Systems and methods for preventing, mitigating, and/or treating dementia

ABSTRACT

The present disclosure provides systems and methods for at least one of preventing, reducing, and treating a level of or change in at least one of amyloid-β (Aβ) peptide, C-terminal fragment-β (β-CTF), β-secretase (BACE1), γ-secretase, neuroinflammation, and/or dementia (e.g., Alzheimer&#39;s disease or age-related decline) in a subject by inducing synchronized gamma oscillations in the brain of the subject using, for example, a stimulus-emitting device to emit a stimulus (e.g., light, sound, and/or haptic) at a frequency (e.g., about 40 Hz) that synchronously activates in vivo a specific cell type (e.g., fast-spiking-parvalbumin (FS-PV) immunoreactive interneurons) and/or brain region (e.g., a sensory cortex and/or hippocampus) of the subject.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the priority benefit, under 35 U.S.C. §119(e),of U.S. Application No. 62/259,187, entitled “System and Methods forPreventing, Mitigating, and/or Treating Dementia,” filed on Nov. 24,2015, the disclosure of which is incorporated herein by reference in itsentirety.

GOVERNMENT SUPPORT STATEMENT

This invention was made with Government support under Grant No. RF1AG047661 awarded by the National Institutes of Health. The Governmenthas certain rights in the invention.

TECHNICAL FIELD

The present disclosure relates generally to systems and methods forpreventing, mitigating, and/or treating dementia in a subject. Morespecifically, the present disclosure relates to systems and methods forinducing synchronized gamma oscillations in at least one brain region ofsubject.

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative diseasecharacterized by a decline in memory, orientation, and reasoning. It isthe most common form of dementia in the world, affecting approximatelyone in eight people over the age of 65, and the sixth leading cause ofdeath in the United States. The prevalence of this progressiveneurodegenerative disorder is estimated to increase by 40% in the nextten years.

Histopathologically, AD may be characterized by the accumulation ofamyloid plaques comprising the amyloid-β (Aβ) peptide andneurofibrillary tangles (NFTs) made of the tau protein. The Aβ peptideis a 36-43 amino acid protein whose normal physiological functionremains unidentified. The Aβ peptide is formed by the sequentialproteolytic cleavage of the amyloid precursor protein (APP) byβ-secretase 1 (BACE1) and γ-secretase. C-terminal fragment β (β-CTF) isan APP derivative produced during amyloidogenic cleavage of APP by BACE1and thus another indicator of Aβ peptide production. Under normalconditions, the soluble Aβ peptide is produced and secreted by neuronsand subsequently cleared from the brain via cerebral spinal fluid (CSF)pathways. However, in subjects with AD, the Aβ peptide appears toaggregate into higher-order species to form soluble oligomers andinsoluble plaques in a concentration-dependent manner. This aggregationmay initiate many neurotoxic events including disrupted brainmetabolism, neuroinflammation, reduced functional connectivity, synapticand neuronal loss, and/or formation of NFTs.

A fundamental relationship between Aβ concentration and neuronalactivity has been demonstrated. First, treatment of organotypichippocampal slices prepared from transgenic (Tg) mice overexpressing APPwith tetrodotoxin decreased neuronal activity and subsequently Aβlevels. Then, the opposite effect—increased neuronal activity—wasobserved upon treatment with picrotoxin. Dynamic modulation of the Aβpeptide concentration and eventual plaque deposition in vivo also hasbeen demonstrated using neuronal activity. In human AD patients, neuralimaging shows that the most severe plaque deposition may align with themost consistently active brain areas, known as the “default-modenetwork.”

Currently AD has no cure, and treatment options do not inhibit thepathological progression of AD, are mainly palliative, and/or may havemultiple, troubling side effects. For example, preventative and/ortherapeutic strategies targeting the Aβ peptide and/or its precursors(e.g., Aβ immunotherapy and inhibition of β- and γ-secretases) have beentoxic and/or ineffective at reducing AD pathology in clinical trials.Clinical trials involving amyloid beta vaccines (e.g., bapineuzumab)have failed due to lack of cognitive benefit. Gamma-secretase inhibitors(e.g., semagacestat) have failed clinical trials for worsening ofcognitive deficits in subjects. Even existing medications likeacetylcholinesterase inhibitors (e.g., donepezil and rivastigmine) andN-methyl-D-aspartate (NMDA)-receptor antagonists (e.g., memantine)demonstrate only mild cognitive benefits.

SUMMARY

Key microscopic pathological hallmarks of AD include the presence ofamyloid plaques, NFTs, and extensive neuronal loss. This accumulation ofneuronal insults occurs over a length of time and induces macroscopiccircuit dysfunctions in the brain, specifically gamma power deficitsduring memory and attention tasks. These gamma oscillations (e.g., about20 Hz to about 100 Hz, about 20 Hz to about 80 Hz, or about 20 Hz toabout 50 Hz) primarily originate, and are modulated by,fast-spiking-parvalbumin (FS-PV)-interneurons.

In one aspect, the present disclosure provides devices, methods, andsystems for preventing, mitigating, and/or treating dementia in asubject comprising inducing synchronized gamma oscillations in at leastone brain region of the subject. In some embodiments, the dementia isassociated with AD, vascular dementia, frontal temporal dementia, LewyBody dementia, and/or age-related cognitive decline. The subject may bea human or an animal.

In some embodiments, the synchronized gamma oscillations have afrequency of about 20 Hz to about 50 Hz, such as about 40 Hz. Thesynchronized gamma oscillations may be induced in a cell-type specificmanner. For example, the oscillations may correspond to synchronizedactivation of FS-PV-interneurons. The synchronized gamma oscillationsmay be induced in a brain-region specific manner. For example, theoscillations may correspond to synchronized activation in at least oneof a hippocampus region and a sensory cortex region.

In one embodiment, a method for preventing, mitigating, and/or treatingdementia in a subject includes the steps of controlling astimulus-emitting device to emit a stimulus and exposing the subject tothe stimulus and/or administering the stimulus to the subject, therebyinducing in vivo synchronized gamma oscillations in at least one brainregion of the subject. The stimulus may have a frequency of about 35 Hzto about 45 Hz, such as a frequency of about 40 Hz. Thestimulus-emitting device may be a haptic device, a light-emittingdevice, and/or a sound-emitting device. For example, the light-emittingdevice may be a fiber optic device. The duration of the exposure of thesubject to the stimulus and/or the administration of the stimulus to thesubject may be about one hour. The exposure of the subject to thestimulus and/or the administration of the stimulus to the subject may berepeated over a time period. For example, the exposure of the subject tothe stimulus and/or the administration of the stimulus to the subjectmay be repeated at least once per day over the time period. The timeperiod may include, but is not limited to, 1 day, 2 days, 3 days, 4days, 5 days, 6 days, one week, two weeks, three weeks, and/or one month(or longer, such as once daily for the rest of the subject's life).

In one aspect, a method for reducing a level (e.g., an amount or rate)of Aβ peptide in at least one brain region of a subject includesinducing synchronized gamma oscillations in the at least one brainregion of the subject. The Aβ peptide may include one or more isoformsof Aβ peptide (e.g., isoform Aβ₁₋₄₀, isoform Aβ₁₋₄₂, and/or isoformAβ₁₋₄₃), soluble Aβ peptide, and/or insoluble Aβ peptide.

In some embodiments, the synchronized gamma oscillations reduceproduction of Aβ peptide in the at least one brain region of the subjectby, for example, reducing a level (e.g., an amount or rate) ofC-terminal fragments (CTFs) and/or N-terminal fragments (NTFs) of APP inthe at least one brain region of the subject. The synchronized gammaoscillations may reduce cleavage of APP into CTFs and NTFs by BACE1and/or γ-secretase in the at least one brain region of the subject. Thesynchronized gamma oscillations may reduce a level (e.g., an number orrate) of endosomes in the at least one brain region of the subject. Forexample, the endosomes may be positive for early endosomal antigen 1(EEA1) and/or Ras-related protein encoded by the RAB5A gene (Rab5). Insome embodiments, the synchronized gamma oscillations promote clearanceof Aβ peptide in the at least one brain region of the subject. Thesynchronized gamma oscillations may increase uptake of Aβ peptide bymicroglia in the at least one brain region of the subject.

In one aspect, a method for increasing a level (e.g., a number or rate)of microglial cells, a morphologic change in the microglial cellsconsistent with a neuroprotective state, and/or an activity of themicroglial cells in at least one brain region of a subject comprisinginducing synchronized gamma oscillations in the at least one brainregion of the subject. The synchronized gamma oscillations mayupregulate at least one differentially expressed gene, such as Nr4a1,Arc, Npas4, Cd68, B2m, Bsr2, Icam1, Lyz2, Irf7, Spp1, Csf1r, and/orCsf2ra, involved in the microglia activity in the at least one brainregion of the subject. The morphologic change in the microglial cellsconsistent with the neuroprotective state may include an increase incell body size and/or a decrease in process length.

In one aspect, a method for reducing a level (e.g., an amount or rate)of Aβ peptide in a hippocampus of a subject includes optogeneticallystimulating FS-PV-interneurons in the hippocampus with a plurality oflight pulses, the FS-PV-interneurons expressing an optogenetic actuator,thereby entraining in vivo synchronized gamma oscillations measured bylocal field potentials in the excitatory neurons (e.g.,FS-PV-interneurons) that reduce the level of Aβ peptide in thehippocampus. The light pulses may have a pulse frequency of about 40pulses/s. Each light pulse may have a duration of about 1 ms. At leastone light pulse may have a wavelength of about 473 nm. The optogeneticactuator may include channelrhodopsin, halorhodopsin, and/orarchaerhodopsin. For example, the optogenetic actuator may bechannelrhodopsin-2 (ChR2).

In one aspect, a method for reducing a level (e.g., an amount or rate)soluble and/or insoluble Aβ peptide in a visual cortex of a subjectincludes stimulating the subject with a plurality of light pulses at apulse frequency of about 40 pulses/s, thereby inducing in vivosynchronized gamma oscillations in the visual cortex that reduce thelevel of the soluble and/or insoluble Aβ peptide in the visual cortex.

In one aspect, a method for reducing a level of (e.g., an amount orrate) tau phosphorylation in a visual cortex of a subject includesstimulating the subject with a plurality of light pulses at a pulsefrequency of about 40 pulses/s, thereby inducing in vivo synchronizedgamma oscillations in the visual cortex that reduce tau phosphorylationin the visual cortex.

In one aspect, a method for reducing a level (e.g., an amount or rate)of Aβ peptide in a hippocampus and/or an auditory cortex of a subjectincludes stimulating the subject with a plurality of sound pulses at apulse frequency of about 40 pulses/s, thereby inducing in vivosynchronized gamma oscillations in the at least one of the hippocampusand the auditory cortex that reduce the level of Aβ peptide in the atleast one of the hippocampus and the auditory cortex.

In one aspect, a system for preventing, reducing, and/or treating alevel (e.g., an amount or rate) of or change in Aβ peptide,neuroinflammation, and/or cognitive function in a subject includes astimulus-emitting device for in vivo synchronized activation of a brainregion of the subject, at least one memory for storing stimulusparameters and processor executable instructions, and at least oneprocessor communicatively connected to the stimulus-emitting device andthe at least one memory. Upon execution of the processor executableinstructions, the at least one processor controls the stimulus-emittingdevice to emit the stimulus according to the stimulus parameters, theparameters including a frequency that synchronously activates the brainregion at the frequency, whereby the Aβ peptide, the neuroinflammation,and/or the dementia in the subject is prevented, reduced, and/ortreated. The frequency may be from about 35 Hz to about 45 Hz, such asabout 40 Hz. The in vivo synchronized activation may be regulated by anenzyme and/or occur in a specific cell type, such as immunoreactiveFS-PV-interneurons. The enzyme may include an optogenetic activator, amicrobial opsin, ChR2, and/or vector AAV-DIO-ChR2-EYFP.

In one aspect, a system for preventing, reducing, and/or treating alevel (e.g., an amount or rate) of or change in Aβ peptide,neuroinflammation, and/or cognitive function in a subject includes alight occlusion device for reducing ambient light to at least one eye ofthe subject and/or a noise-canceling device for reducing ambient noiseto at least one ear of the subject. The light occlusion device mayinclude a light-emitting unit for emitting a light stimulus to the atleast one eye for in vivo synchronized activation of at least one of avisual cortex and a hippocampus of the subject. The noise-cancelingdevice may include a speaker unit for emitting a sound stimulus to theat least one ear for in vivo synchronized activation of at least one ofan auditory cortex and a hippocampus of the subject. The system alsoincludes at least one memory for storing processor executableinstructions and at least one processor communicatively connected to thelight occlusion device and/or the noise-canceling device and the atleast one memory. Upon execution of the processor executableinstructions, the at least one processor may control the light occlusiondevice such that the light-emitting unit emits the light stimulus at afrequency that synchronously activates the at least one of the visualcortex and the hippocampus at the frequency. Alternatively, or inaddition, the at least one processor may control the noise-cancelingdevice such that the speaker unit actuates the sound stimulus at thefrequency that synchronously activates the at least one of the auditorycortex and the hippocampus at the frequency.

In one aspect, a method for improving cognitive function in a subjectincludes controlling at least one electroacoustic transducer to convertan electrical audio signal into a corresponding sound stimulus. In someembodiments, the sound stimulus includes a click train with a clickfrequency of about 35 clicks/s to about 45 clicks/s. The method furtherincludes exposing the subject to the sound stimulus and/or administeringthe stimulus to the subject to induce synchronized gamma oscillations inat least one brain region of the subject, the synchronized gammaoscillations resulting in an improvement of the cognitive function inthe subject. The cognitive function may include recognition,discrimination, and/or spatial memory.

In one aspect, a method for preventing, reducing, and/or treating alevel (e.g., an amount or rate) of or change in Aβ peptide,neuroinflammation, and/or cognitive function in a subject includescontrolling at least one electroacoustic transducer to convert anelectrical audio signal into a corresponding sound stimulus, the soundstimulus including a click train with a click frequency of about 35clicks/s to about 45 clicks/s, and exposing the subject to the soundstimulus and/or administering the stimulus to the subject to inducesynchronized gamma oscillations in at least one brain region of thesubject, the synchronized gamma oscillations resulting in theprevention, the reduction, and/or the treatment of the level of Aβpeptide, neuroinflammation, and/or dementia in the subject.

The Aβ peptide may include one or more isoforms of Aβ peptide (e.g.,isoform Aβ₁₋₄₀, isoform Aβ₁₋₄₂, and/or isoform Aβ₁₋₄₃), soluble Aβpeptide, and/or insoluble Aβ peptide. The synchronized gammaoscillations may prevent, reduce, and/or treat the level of Aβ peptide,neuroinflammation, and/or dementia in the subject by increasing a numberof microglial cells in the at least one brain region of the subjectand/or enhancing uptake of Aβ peptide by the microglial cells in the atleast one brain region. The at least one brain region may include theauditory cortex and/or the hippocampus.

The click frequency may be about 40 clicks/s. Each click in the clicktrain may have a duration of about 1 ms. Each click in the click trainmay have a frequency of about 10 Hz to about 100 kHz, about 12 Hz toabout 28 kHz, about 20 Hz to about 20 kHz, and/or about 2 kHz to about 5kHz. Each click in the click train may have a sound pressure level ofabout 0 dB to about 85 dB, about 30 dB to about 70 dB, and about 60 dBto about 65 dB.

The at least one electroacoustic transducer may include at least oneheadphone, in which case the method may include applying the at leastone headphone around, on, and/or in at least one ear of the subject todirect the sound stimulus into the at least one ear of the subject. Themethod also may include reducing ambient noise using passive noiseisolation and/or active noise cancellation.

In one aspect, a system for preventing, reducing, and/or treating alevel (e.g., an amount or rate) of or change in Aβ peptide,neuroinflammation, and/or cognitive function in a subject includes atleast one electroacoustic transducer for converting an electrical audiosignal into a corresponding sound stimulus, the sound stimulus includinga click train with a click frequency of about 35 clicks/s to about 45clicks/s, at least one memory device for storing the electrical audiosignal and processor executable instructions, and at least one processorcommunicatively connected to the at least one electroacoustic transducerand the at least one memory device. Upon execution of the processorexecutable instructions, the at least one processor controls theelectroacoustic transducer to output the sound stimulus to at least oneear of the subject to induce synchronized gamma oscillations in at leastone brain region of the subject, the synchronized gamma oscillationsresulting in the prevention, the reduction, and/or the treatment of thelevel of Aβ peptide, neuroinflammation, and/or dementia in the subject.

The system may be stationary or portable. If the at least oneelectroacoustic transducer includes at least one headphone for thesubject to wear around, on, and/or in the at least one ear to direct thesound stimulus into the at least one ear of the subject and reduceambient noise, the system further may include a headphone interface forcommunicating the electrical audio signal to the at least one headphone.Alternatively, or in addition, the system may include a neuroimagingscanner to monitor function in the at least one brain region of thesubject before, during, and/or following the output of the soundstimulus.

In one aspect, a method for preventing, mitigating, and/or treatingdementia in a subject includes providing a device that inducessynchronized gamma oscillations in at least one brain region of thesubject.

In one aspect, a method for maintaining and/or reducing a blood level(e.g., an amount) of a glucocorticoid involved in a stress response in asubject includes providing a device that induces synchronized gammaoscillations in at least one brain region of the subject.

In one aspect, a method for preventing and/or reducing anxiety in asubject includes providing a device that induces synchronized gammaoscillations in at least one brain region of the subject.

In one aspect, a method for maintaining and/or enhancing a memoryassociation includes providing a device that induces synchronized gammaoscillations in at least one brain region of the subject. The memoryassociation may be based in spatial memory.

In one aspect, a method for a maintaining and/or enhancing cognitiveflexibility includes providing a device that induces synchronized gammaoscillations in at least one brain region of the subject.

In one aspect, a method for maintaining and/or reducing changes toanatomy and/or morphology in at least one brain region of a subjectincludes providing a device that induces synchronized gamma oscillationsin the at least one brain region of the subject. The anatomy and/ormorphology may include brain weight, lateral ventricle size, a thicknessof a cortical layer, a thickness of a neuronal layer, and/or a bloodvessel diameter. The at least one brain region may include a visualcortex, a somatosensory cortex, and/or an insular cortex of the subject.

In one aspect, a method for maintaining and/or reducing changes to anumber of neurons, a quality of DNA in the neurons, and/or a synapticpuncta density in at least one brain region of a subject includesproviding a device that induces synchronized gamma oscillations in theat least one brain region of the subject. The at least one brain regionmay include a visual cortex, a somatosensory cortex, an insular cortex,and/or a hippocampus of the subject.

In one aspect, a device that induces synchronized gamma oscillations inat least one brain region of a subject can prevent, mitigate, and/ortreat dementia and/or anxiety in the subject, maintain and/or enhance amemory association and/or cognitive flexibility of the subject, and/ormaintain and/or reduce changes to anatomy, morphology, cells, andmolecules in the at least one brain region of the subject.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts discussed in greater detail below (provided suchconcepts are not mutually inconsistent) are contemplated as being partof the inventive subject matter disclosed herein. In particular, allcombinations of claimed subject matter appearing at the end of thisdisclosure are contemplated as being part of the inventive subjectmatter disclosed herein. It should also be appreciated that terminologyexplicitly employed herein that also may appear in any disclosureincorporated by reference should be accorded a meaning most consistentwith the particular concepts disclosed herein.

Other systems, processes, and features will become apparent to thoseskilled in the art upon examination of the following drawings anddetailed description. It is intended that all such additional systems,processes, and features be included within this description, be withinthe scope of the present invention, and be protected by the accompanyingclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the drawings primarily are forillustrative purposes and are not intended to limit the scope of theinventive subject matter described herein. The drawings are notnecessarily to scale; in some instances, various aspects of theinventive subject matter disclosed herein may be shown exaggerated orenlarged in the drawings to facilitate an understanding of differentfeatures. In the drawings, like reference characters generally see,e.g., like features (e.g., functionally similar and/or structurallysimilar elements).

FIG. 1 is a schematic diagram illustrating a mouse running through avirtual linear maze on a spherical treadmill in accordance with someembodiments.

FIGS. 2A and 2B are electrical traces recorded from hippocampal CA1 andillustrating theta oscillations and sharp-wave ripples (SWRs) inaccordance with some embodiments.

FIGS. 3A and 3B are plots illustrating the mean and standard deviationof normalized power spectrum and normalized power spectral densitiesduring theta periods in three-month-old Tg 5×FAD and wild-type (WT) micein accordance with some embodiments.

FIGS. 4A and 4B are spectrograms illustrating SWRs for a WT mouse and a5×FAD mouse in accordance with some embodiments.

FIGS. 5A-5C are plots depicting the distribution of instantaneous gammafrequencies during SWRs in accordance with some embodiments.

FIG. 6A is a series of graphs depicting the Z-scored gamma power as afunction of the time from the peak of the SWRs in 5×FAD and WT mice inaccordance with some embodiments. FIG. 6B is a plot depicting thecumulative distribution of gamma power during SWRs in 5×FAD and WT micein accordance with some embodiments. FIGS. 6C and 6D are plots depictingthe cumulative distribution of the Z-scored gamma power during the 100ms around the peak of the SWRs for WT and 5×FAD mice in accordance withsome embodiments. FIG. 6E is a plot depicting the cumulativedistribution of gamma power during large SWRs in 5×FAD and WT mice inaccordance with some embodiments.

FIG. 7A is a plot depicting fraction of spikes as function of phase ofgamma oscillation, and FIG. 7B is a plot depicting depth of modulationof spiking during SWRs in accordance with some embodiments. FIGS. 7C and7D are plots illustrating fraction of spikes in hippocampal CA1 duringSWRs as a function of phase of gamma oscillations in accordance withsome embodiments. FIG. 7E is a plot depicting fraction of spikes asfunction of phase of gamma oscillation, and FIG. 7F is a plot depictingdepth of modulation of spiking during large SWRs in accordance with someembodiments.

FIGS. 8A and 8B are plots depicting SWR rate per non-theta period in5×FAD and WT animals for each animal and all animals combined inaccordance with some embodiments.

FIG. 9 is a schematic diagram illustrating a viral vector for regulatingactivation of a specific cell type in the brain of a subject inaccordance with some embodiments.

FIGS. 10A and 10B are schematic diagrams illustrating delivery of asignal to the CA1 region of the hippocampus of a subject in accordancewith some embodiments.

FIG. 11 is an immunofluorescence image illustrating immunostaining ofneural tissue in a subject with ChR2 and DAPI in accordance with someembodiments.

FIG. 12A is an immunofluorescence image illustrating ChR2-EYFP expressedin PV+ interneurons in accordance with some embodiments. FIG. 12B is aseries of immunofluorescence images illustrating immunohistochemistrywith anti-EYFP and anti-PV antibodies in accordance with someembodiments.

FIGS. 13A and 13B include a schematic diagram of a study, an electricaltrace of a local field potential, and power spectral density ofFS-PV-interneurons in accordance with some embodiments.

FIGS. 14A and 14B include a raw electrical trace, the trace filtered forspikes after optogenetic stimulation, and plots of spike probabilityafter the onset of 1 ms laser pulse in accordance with some embodiments.

FIG. 15A is a histogram illustrating the difference in firing ratesbetween 40-Hz stimulation and random stimulation periods in accordancewith some embodiments. FIG. 15B is a bar graph illustrating multiunitfiring rates per 40-Hz stimulation, random stimulation, and nostimulation periods for each animal in accordance with some embodiments.

FIG. 16A is an electrical trace recorded from a hippocampus of a subjectduring a frequency-specific increase in the stimulation of a specificcell type in the CA1 region of the hippocampus of a subject inaccordance with some embodiments. FIG. 16B is a plot of power spectraldensity illustrating a frequency-specific increase in the local fieldpotential power in the stimulation of a specific cell type in the CA1region of the hippocampus of a subject in accordance with someembodiments.

FIGS. 17A and 17B are bar graphs depicting relative Aβ₁₋₄₀ and Aβ₁₋₄₂levels of 5×FAD/PV-Cre CA1 by one-way ANOVA in accordance with someembodiments.

FIGS. 18A and 18B are bar graphs depicting relative Aβ₁₋₄₀ and Aβ₁₋₄₂levels of 5×FAD/αCamKII-Cre CA1 by one-way ANOVA in accordance with someembodiments.

FIG. 19A is a series of images illustrating immunohistochemistry withanti-Aβ and anti-EEA1 antibodies in hippocampal CA1 region in accordancewith some embodiments. FIG. 19B is a series of bar graphs depicting therelative immunoreactivity of Aβ normalized to EYFP in accordance withsome embodiments.

FIG. 20A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Aβ antibodies in hippocampal CA1 regionof 5×FAD/PV-Cre in accordance with some embodiments. FIG. 20B is a bargraph depicting the relative immunoreactivity of Aβ normalized to EYFPin accordance with some embodiments.

FIG. 21A is a representative western blot depicting levels of APP(CT695), APP NTF (A8967), APP CTFs (CT695), and β-Actin (A5316) (loadingcontrol) in CA1 in accordance with some embodiments. FIG. 21B is a bargraph depicting relative (normalized to actin) immunoreactivity of APPCTFs in 40-Hz vs. EYFP and Random conditions in accordance with someembodiments. FIG. 21C is a series of western blots depicting levels offull-length APP 2106 (CT695), APP CTFs 2108 (CT695) and β-Actin 2112(A5316, loading control) in CA1 in accordance with some embodiments.

FIG. 22A is a bar graph depicting relative (normalized to actin)immunoreactivity of APP NTFs in 40-Hz versus EYFP and Random conditionsin accordance with some embodiments.

FIG. 22B is a bar graph depicting relative (normalized to actin)immunoreactivity of full-length APP in EYFP, random, and 40-Hzconditions in accordance with some embodiments.

FIG. 23 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Rab5 (ADI-KAp-GP006-E) antibody inaccordance with some embodiments.

FIG. 24A is a bar graph representing the relative immunoreactivity ofEEA1 normalized to EYFP, and FIG. 24B is a bar graph depicting relativeRab5 intensity levels of CA1 from 5×FAD/PV-Cre under EYFP, 40 Hz, andrandom stimulation conditions in accordance with some embodiments.

FIG. 25A is a bar graph depicting levels of the Aβ peptide isoformAβ₁₋₄₀ following different types of stimulation of the CA1 region of thehippocampus of a subject in accordance with some embodiments. FIG. 25Bis a bar graph depicting a decrease in the Aβ peptide isoform Aβ₁₋₄₂following stimulation of a specific cell type in the CA1 region of thehippocampus of a subject with gamma oscillations in accordance with someembodiments. FIG. 25C is a series of images illustrating a decrease inthe level of CTFs (e.g., β-CTF) and an increase in the level offull-length APP (normalized to actin) following stimulation of aspecific cell type in the CA1 region of the hippocampus of a subjectwith gamma oscillations in accordance with some embodiments.

FIGS. 26A-26B are immunofluorescence images illustrating endosome levels(based on EEA1 levels) following different types of stimulation of theCA1 region of the hippocampus of a subject in accordance with someembodiments.

FIG. 27 is a bar graph depicting mean intensity values (normalized toFAD) for the immunofluorescence images in FIGS. 6A-6B followingdifferent types of stimulation of the CA1 region of the hippocampus of asubject in accordance with some embodiments.

FIG. 28 is a heat map presenting differentially expressed genesdetermined by whole transcriptome ribonucleic acid sequencing (RNA-seq)of mouse hippocampal CA1 region with and without 40-Hz stimulation inaccordance with some embodiments.

FIG. 29 is a box plot illustrating FPKM values of up- and down-regulatedgenes in EYFP and 40-Hz conditions in accordance with some embodiments.

FIG. 30 is a pie chart illustrating cell-type specific expressionpatterns of identified up-regulated genes following 40-Hz stimulation inaccordance with some embodiments.

FIG. 31 is a bar graph illustrating RT-qPCR verification of specificgene targets in the RNA-seq data set in accordance with someembodiments.

FIGS. 32A and 32B are plots illustrating power spectral densities oflocal field potentials recoded above the brain during 40-Hz lightflicker show in accordance with some embodiments.

FIG. 33 is a bar graph depicting RT-qPCR verification of specific genetargets in the RNA-seq data set in accordance with some embodiments.

FIG. 34 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Iba1 (019-19741) and anti-Aβ (12F4)antibodies in hippocampal CA1 region of 5×FAD/PV-Cre mice in EYFP,40-Hz, and Random stimulation conditions in accordance with someembodiments.

FIG. 35A is a bar graph depicting the number of microglia in EYFP and40-Hz conditions in accordance with some embodiments. FIG. 35B is a bargraph depicting the diameter of microglial cell bodies normalized toEYFP in EYFP, 40-Hz, and Random stimulation conditions in accordancewith some embodiments. FIG. 35C is a bar graph depicting the averagelength of microglia primary processes normalized to EYFP in EYFP, 40-Hz,and Random stimulation conditions in accordance with some embodiments.FIG. 35D is a bar graph depicting the percent of Iba1-positive(microglia) cell bodies that are also Aβ-positive in EYFP and 40-Hzstimulation conditions in accordance with some embodiments.

FIG. 36 is a series of 3D rendering formed by merging immunofluorescenceimages from FIG. 34 in accordance with some embodiments.

FIG. 37A is a series of immunofluorescence images illustratingimmunohistochemistry with Hoechst in hippocampal CA1 region of5×FAD/PV-Cre in accordance with some embodiments. FIG. 37B is a bargraph depicting the estimated CA1 thickness of 5×FAD/PV-Cre in EYFP and40-Hz stimulation conditions in accordance with some embodiments.

FIG. 38A is a heat map displaying differentially expressed genes (DEGs)determined by genome-wide RNA-seq of hippocampal CA1 upon 40-Hz FS-PV+stimulation or control stimulation in accordance with some embodiments.FIG. 38B is a chart illustrating overlap between DEGs up-regulated inthe TREAT condition in FIG. 38A in accordance with some embodiments.

FIG. 39 is a bar graph depicting RT-qPCR verification of specific genetargets in the RNA-seq data set of FIG. 38A in accordance with someembodiments.

FIG. 40 is a plot illustrating the biological processes to which theup-regulated genes of FIG. 38A relate in accordance with someembodiments.

FIG. 41 is a plot illustrating the biological processes to which thedown-regulated genes of FIG. 38A relate in accordance with someembodiments.

FIG. 42A is a series of immunofluorescence images illustrating levels ofIba1 following different types of stimulation of the CA1 region of thehippocampus of a subject in accordance with some embodiments. FIG. 42Bis a bar graph depicting mean intensity values for theimmunofluorescence images in FIG. 42A in accordance with someembodiments.

FIG. 43A is a schematic diagram illustrating a mouse exposed to lightflicker stimulation in accordance with some embodiments. FIG. 43Bincludes a local field potential trace in the visual cortex before andduring 40-Hz light flicker and a plot of power spectral density inaccordance with some embodiments. FIGS. 43C-43F are plots depictingpower spectral densities of local field potentials in the visual cortexin accordance with some embodiments.

FIG. 44A is a series of histograms depicting fraction of spikes invisual cortex as a function of time for four cycles of 40-Hz lightflicker and an equivalent period of time for random light flicker inaccordance with some embodiments. FIG. 44B is a series of electricaltraces of local field potentials recorded above the brain during lightflicker in accordance with some embodiments.

FIG. 45A is a histogram illustrating the difference in firing ratesbetween 40-Hz light flicker and random light flicker in accordance withsome embodiments. FIG. 45B is a plot illustrating multi-unit firingrates in visual cortex in accordance with some embodiments.

FIG. 46A is a schematic diagram illustrating an experimental paradigm inaccordance with some embodiments. FIGS. 46B-46C are plots furtherillustrating changes in baseline levels of Aβ peptide isoforms Aβ₁₋₄₀and Aβ₁₋₄₂, respectively, following the experimental paradigm in FIG.46A in accordance with some embodiments.

FIGS. 47A and 47B are bar graphs depicting changes in baseline levels ofAβ₁₋₄₀ and Aβ₁₋₄₂, respectively, in 5×FAD visual cortex in accordancewith some embodiments.

FIG. 48A is a bar graph depicting changes in baseline levels of Aβ₁₋₄₀and Aβ₁₋₄₂ in 5×FAD barrel cortex under dark and 40-Hz flickerconditions in accordance with some embodiments. FIG. 48B is a bar graphdepicting changes in baseline levels of Aβ₁₋₄₀ and Aβ₁₋₄₂ in APP/PS1visual cortex under dark and 40-Hz flicker conditions in accordance withsome embodiments. FIG. 48C is a bar graph depicting changes in baselinelevels of Aβ₁₋₄₀ and Aβ₁₋₄₂ in WT visual cortex under dark and 40-Hzflicker conditions in accordance with some embodiments.

FIG. 49 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Iba1 (019-19741) and anti-Aβ (12F4)antibodies in 5×FAD visual cortex under dark and 40-Hz flickerconditions in accordance with some embodiments.

FIG. 50A is a bar graph depicting the number Iba1-positive cells(microglia) in accordance with some embodiments. FIG. 50B is a bar graphdepicting the diameter of microglial cell bodies normalized to controlunder dark and 40-Hz flicker conditions in accordance with someembodiments. FIG. 50C is a bar graph depicting the average length ofmicroglia primary processes normalized to control under dark and 40-Hzflicker conditions in accordance with some embodiments. FIG. 50D is abar graph depicting the percentage of microglia that are alsoAβ-positive under dark and 40-Hz flicker conditions in accordance withsome embodiments.

FIG. 51 is a series of 3D renderings (from immunofluorescence images) ofIba+ microglia under dark and 40-Hz flicker conditions fromCLARITY-treated 100 μm tissue sections in accordance with someembodiments. CLARITY is a method of making brain tissue transparentusing, e.g., acrylamide-based hydrogels built from within, and linkedto, the tissue.

FIG. 52A is a flow diagram illustrating a method of isolating microgliafrom a visual cortex using fluorescence-activated cell sorting (FACS) inaccordance with some embodiments.

FIG. 52B is a bar graph depicting Aβ₁₋₄₀ levels in microglia isolatedfrom the visual cortices of three-month-old 5×FAD and WT control animalsusing the method of FIG. 52A in accordance with some embodiments.

FIG. 53A is a series of immunofluorescence images illustratingimmunohistochemistry with SVP38 antibodies to detect synaptophysin inthree-month-old 5×FAD visual cortex under dark and 40-Hz flickerconditions in accordance with some embodiments. FIG. 53B is a bar graphdepicting relative SVP38 intensity levels of 5×FAD visual cortex afterdark and 40-Hz light flicker conditions in accordance with someembodiments.

FIG. 54A is a bar graph illustrating a decrease in the Aβ peptideisoform Aβ₁₋₄₂ following stimulation of the visual cortex of a subjectwith gamma oscillations in accordance with some embodiments. FIG. 54B isa bar graph illustrating levels of the Aβ peptide isoform Aβ₁₋₄₂ afterstimulation of the visual cortex of a subject with gamma oscillationsand again twenty-four hours after the stimulation in accordance withsome embodiments.

FIG. 55A includes an electrical trace of a local field potential in thehippocampus before and during 40-Hz light flicker and a plot of powerspectral densities in accordance with some embodiments. FIG. 55B is aseries of histograms of fractions of spikes in the hippocampus as afunction of time for 4 cycles of 40-Hz light flicker and the equivalentperiod of time for random light flicker, respectively, in accordancewith some embodiments.

FIG. 56A is a histogram illustrating the difference in firing ratesbetween 40-Hz light flicker and random light flicker in accordance withsome embodiments. FIG. 56B is a plot illustrating multi-unit firingrates in CA1 during 40-Hz light flicker in accordance with someembodiments.

FIG. 57A is a bar graph depicting relative Aβ₁₋₄₀ levels in 5×FAD visualcortex in accordance with some embodiments. FIG. 57B is a bar graphdepicting relative Aβ₁₋₄₂ levels in 5×FAD visual cortex in accordancewith some embodiments.

FIG. 58A is a bar graph depicting relative Aβ₁₋₄₀ levels in 5×FAD visualcortex with recovery after 40-Hz light flicker in accordance with someembodiments. FIG. 58B is a bar graph depicting relative Aβ₁₋₄₂ levels in5×FAD visual cortex with recovery after 40-Hz light flicker inaccordance with some embodiments.

FIG. 59A is a schematic diagram illustrating a study in accordance withsome embodiments. FIG. 59B is a bar graph depicting relative Aβ₁₋₄₂levels in visual cortices of six-month-old 5×FAD mice after seven daysof one hour/day under dark or 40-Hz flicker conditions in accordancewith some embodiments. FIG. 59C is a bar graph illustrating relativeAβ₁₋₄₀ levels in visual cortices of six-month-old 5×FAD mice after sevendays of one hour/day under dark or 40-Hz flicker conditions inaccordance with some embodiments.

FIG. 60A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Aβ antibody in visual cortices ofsix-month-old 5×FAD mice after seven days of one hour/day under dark or40-Hz flicker conditions in accordance with some embodiments. FIG. 60Bis bar graph depicting the number of Aβ-positive plaque deposits afterseven days of one hour/day under dark or 40-Hz flicker conditions invisual cortices of six-month-old 5×FAD mice in accordance with someembodiments. FIG. 60C is a bar graph depicting the area of Aβ-positiveplaques after seven days of one hour/day under dark or 40-Hz flickerconditions in visual cortices of six-month-old 5×FAD mice in accordancewith some embodiments.

FIG. 61A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-phosphoTau (S202) and anti-MAP2antibodies in four-month-old P301S mice after seven days of one hour/dayunder dark or 40-Hz flicker conditions in accordance with someembodiments. FIG. 61B is a bar graph depicting relative phosphoTau(pTau) (S202) intensity levels of P301S visual cortex after seven daysof one hour/day under dark and 40-Hz flicker conditions in accordancewith some embodiments. FIG. 61C is a bar graph depicting relative MAP2intensity levels of P301S visual cortex after seven days of one hour/dayunder dark and 40-Hz flicker conditions in accordance with someembodiments.

FIG. 62A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-pTau 6202(S404) antibodies in 4-month-oldP301S mice after seven days of one hour/day under dark and 40-Hz flickerconditions in accordance with some embodiments. FIG. 62B is a bar graphdepicting relative pTau (S400/T403/S404) fluorescence intensity levelsof P301S visual cortex after seven days of one hour/day under dark and40-Hz flicker conditions in accordance with some embodiments.

FIG. 63A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-pTau 6302 (S396) antibodies infour-month-old P301S mice after seven days of one hour/day under darkand 40-Hz flicker conditions in accordance with some embodiments. FIG.63B is a bar graph depicting relative pTau (S396) fluorescence intensitylevels of P301S visual cortex after seven days of one hour/day underdark and 40-Hz flicker conditions in accordance with some embodiments.

FIG. 64 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Iba1 antibodies in four-month-old P301Smice after seven days of one hour/day under dark and 40-Hz flickerconditions in accordance with some embodiments.

FIG. 65A is a bar graph depicting the number of microglia after sevendays of one hour/day under dark and 40-Hz flicker conditions inaccordance with some embodiments. FIG. 65B is a bar graph depicting thediameter of microglial cell bodies normalized to control after sevendays of one hour/day under dark and 40-Hz flicker conditions inaccordance with some embodiments. FIG. 65C is a bar graph depicting theaverage length of microglia primary processes normalized to controlafter seven days of one hour/day under dark and 40-Hz flicker conditionsin accordance with some embodiments.

FIG. 66 is a plot illustrating levels of soluble and insoluble Aβpeptide isoforms Aβ₁₋₄₀ and Aβ₁₋₄₂ in the visual cortex of a subjectwith and without visual gamma stimulation in accordance with someembodiments.

FIGS. 67A-67B are plots illustrating whole brain Aβ peptide levels withand without transcranial gamma stimulation of a subject in accordancewith some embodiments.

FIG. 68A is a flow diagram illustrating a study conducted to examinewhether gamma exposure and/or administration in accordance with someembodiments causes stress to subjects.

FIG. 68B is a bar graph depicting levels of corticosterone indicatingstress response in the subjects.

FIG. 69A is a flow diagram illustrating a study conducted to examinewhether gamma exposure and/or administration in accordance with someembodiments reduces anxiety in subjects. FIG. 69B is an imageillustrating an elevated plus maze apparatus. FIGS. 69C and 69D areimages illustrating representative tracks of the subjects during anelevated plus maze session.

FIG. 70 is a bar graph depicting the average time the subjects spentexploring in open arms and closed arms during the elevated plus mazesession.

FIG. 71A is a flow diagram illustrating a study conducted to examinewhether gamma exposure and/or administration in accordance with someembodiments reduces stress and/or anxiety in subjects. FIG. 71B is animage illustrating an open field arena. FIGS. 71C and 71D are imagesillustrating representative tracks of the subjects during an open fieldtest.

FIG. 72A is a plot depicting the average amount of time the subjectsspent in the center of the open field during each minute of the openfield test. FIG. 72B is a bar graph depicting the average total time thesubjects spent in the periphery of the open field during the open fieldtest.

FIGS. 73A and 73B are schematic diagrams illustrating a study conductedto examine whether gamma exposure and/or administration in accordancewith some embodiments alters innate novelty seeking behavior insubjects. FIG. 73C is a bar graph depicting the average amount of timethe subjects spent exploring a first novel object compared to a secondnovel object according to the schematic diagram of FIG. 73A.

FIG. 74 is a plot depicting the average amount of time during eachminute the subjects spent exploring a novel object according to theschematic diagram of FIG. 73B.

FIG. 75A is a flow diagram illustrating a study conducted using a fearconditioning paradigm to examine whether gamma exposure and/oradministration in accordance with some embodiments impacts learning andmemory in subjects. FIG. 75B is a stimulus diagram illustrating a tonetest with altered contexts as a function of time.

FIGS. 76A and 76B are bar graphs demonstrating enhanced memory insubjects in accordance with some embodiments.

FIG. 77A is a flow diagram illustrating a study conducted to examinewhether gamma exposure and/or administration improves memory in subjectsin accordance with some embodiments. FIG. 77B is a diagram illustratinga Morris water maze with a platform hidden in a target quadrant. FIGS.77C and 77D are images illustrating representative tracks of thesubjects during a Morris water maze probe test.

FIG. 78A is a plot depicting the average amount of time the subjectsspent finding the hidden platform in the Morris water maze test on eachday. FIG. 78B is a plot depicting the average amount of time thesubjects spent searching for the removed platform in the target quadrantduring each half minute. FIG. 78C is a plot depicting the average amountof time the subjects spent searching for the removed platform in theopposite quadrant during each half minute.

FIG. 79A is a diagram illustrating a Morris water maze test with aplatform hidden in a first quadrant. FIG. 79B is a diagram illustratinga Morris water maze test with a platform hidden in a second quadrant,opposite the first quadrant, for reversal learning. FIG. 79C is a plotdepicting the average amount of time the subjects spent finding thehidden platform in the Morris water maze reversal learning test on eachday.

FIG. 80A is a flow diagram illustrating a study conducted to examinewhether chronic gamma exposure and/or administration in accordance withsome embodiments influences spatial learning and memory in subjects.FIG. 80B is a plot depicting the average amount of time the subjectsspent finding the hidden platform in the Morris water maze test on eachday. FIG. 80C is a bar graph depicting the average amount of time thesubjects spent searching for the removed platform in the target quadrantduring a thirty-second trial.

FIG. 81A is a flow diagram illustrating the study of FIG. 80A expandedto include reversal learning. FIG. 81B is a plot depicting the averageamount of time the subjects spent finding the hidden platform in theMorris water maze reversal learning test on each day.

FIG. 82A is a bar graph depicting the average amount of time thesubjects spent searching for the removed platform in the target quadrantduring a thirty-second trial. FIG. 82B is a bar graph depicting theaverage amount of time the subjects spent searching for the removedplatform in the opposite quadrant.

FIG. 83 is a timeline diagram of a study conducted to examine the effectof gamma exposure and/or administration in accordance with someembodiments on deoxyribonucleic acid (DNA) damage and neuronal loss inthe visual cortex of a subject.

FIG. 84 is a diagram illustrating groups of subjects for studiesconducted to examine the effect of gamma exposure and/or administrationin accordance with some embodiments.

FIG. 85 is bar graph comparing brain weight change across the groups ofsubjects in FIG. 84 in accordance with some embodiments.

FIG. 86 is bar graph comparing fold change of lateral ventricleexpansion across the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIGS. 87A-87E are images illustrating lateral ventricles representativeof the groups of subjects in FIG. 84 in accordance with someembodiments.

FIGS. 88A-88C are brain anatomy diagrams illustrating brain regions ofinterest in accordance with some embodiments.

FIG. 89 is a bar graph depicting average thickness of the V1-corticallayer across the groups of subjects in FIG. 84 in accordance with someembodiments.

FIG. 90 is a bar graph depicting average thickness of theV1-NeuN-positive cell layer across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIGS. 91A-91E are images illustrating cells with Hoechst labels and/orNeuN labels representative of the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 92 is a bar graph depicting average thickness of the SS1-corticallayer across the groups of subjects in FIG. 84 in accordance with someembodiments.

FIG. 93 is a bar graph depicting average thickness of theSS1-NeuN-positive cell layer across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIGS. 94A-94E are images illustrating cells with Hoechst labels and/orNeuN labels across the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIG. 95 is a bar graph depicting average thickness of the cortical layerof the insular cortex across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 96 is a bar graph depicting average thickness of the NeuN-positivecell layer of the insular cortex across the groups of subjects in FIG.84 in accordance with some embodiments.

FIGS. 97A-97E are images illustrating cells with Hoechst labels and/orNeuN labels representative of the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 98 is a bar graph comparing the amount of visual cortexNeuN-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 99 is bar graph comparing the amount of visual cortexγH2AX-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 100 is a series of images illustrating visual cortex samplesrepresentative of the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIG. 101 is a bar graph comparing the amount of somatosensory cortexNeuN-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 102 is bar graph comparing the amount of somatosensory cortexγH2AX-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 103 is a series of images illustrating somatosensory cortex samplesrepresentative of the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIG. 104 is a bar graph comparing the amount of insular cortexNeuN-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 105 is bar graph comparing the amount of insular cortexγH2AX-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 106 is a series of images illustrating insular cortex samplesrepresentative of the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIG. 107 is a bar graph comparing the amount of hippocampusNeuN-positive cells across the groups of subjects in FIG. 84 inaccordance with some embodiments.

FIG. 108 is bar graph comparing the amount of hippocampus γH2AX-positivecells across the groups of subjects in FIG. 84 in accordance with someembodiments.

FIG. 109 is a series of images illustrating hippocampus samplesrepresentative of the groups of subjects in FIG. 84 in accordance withsome embodiments.

FIG. 110 is a bar graph comparing the visual cortex puncta densityacross the groups of subjects in FIG. 84 in accordance with someembodiments.

FIG. 111 is a bar graph comparing the somatosensory cortex punctadensity across the groups of subjects in FIG. 84 in accordance with someembodiments.

FIG. 112 is a bar graph comparing the insular cortex puncta densityacross the groups of subjects in FIG. 84 in accordance with someembodiments.

FIGS. 113A-113D are images illustrating a Hoechst stain, VGluT1 markers,and/or GAD65 markers in a representative sample in accordance with someembodiments. FIGS. 113E and 113F are images illustrating a method ofpuncta quantification in accordance with some embodiments.

FIG. 114 is a stimulus diagram illustrating a click-train stimulus inaccordance with some embodiments.

FIG. 115 is a flow diagram illustrating a study conducted to examinewhether auditory gamma exposure and/or administration in accordance withsome embodiments induces microglial activation in the auditory corticesof subjects.

FIG. 116A is a bar graph depicting the average number of microglia inthe auditory cortices of subjects in accordance with some embodiments.FIG. 116B is a bar graph depicting fold change of microglial projectionlength in the auditory cortices of subjects in accordance with someembodiments. FIG. 116C is a bar graph depicting the average fold changeof soma size of microglia in the auditory cortices of subjects inaccordance with some embodiments.

FIGS. 117A and 117B are representative images of microglia in theauditory cortices of subjects in accordance with some embodiments.

FIGS. 118A and 118B are magnified images of microglial projection lengthfrom FIGS. 117A and 117B in accordance with some embodiments.

FIGS. 119A and 119B are magnified images of microglial soma size fromFIGS. 117A and 117B in accordance with some embodiments.

FIG. 120A is a bar graph depicting the average number of microglia perimage field in the auditory cortices of subjects in accordance with someembodiments. FIG. 120B is a bar graph depicting the average fold changein soma size of microglia in the auditory cortices of subjects inaccordance with some embodiments. FIG. 120C is a bar graph depicting theaverage fold change in projection length of microglia in the auditorycortices of subjects in accordance with some embodiments.

FIGS. 121A and 121B are representative images of microglia in theauditory cortices of subjects in accordance with some embodiments.

FIGS. 122A-122D are bar graphs depicting levels of soluble AO isoformsAβ₁₋₄₀ and Aβ₁₋₄₂ in the auditory cortices and hippocampuses of subjectsin accordance with some embodiments.

FIGS. 123A-123D are bar graphs depicting levels of insoluble Aβ isoformsAβ₁₋₄₀ and Aβ₁₋₄₂ in the auditory cortices and hippocampuses of subjectsin accordance with some embodiments.

FIGS. 124A-124D are representative images of microglia in the auditorycortices of subjects in accordance with some embodiments.

FIG. 125A is a flow diagram illustrating a novel object recognitiontest. FIG. 125B is a bar graph demonstrating improvements in memory inaccordance with some embodiments.

FIG. 126A is a flow diagram illustrating a novel object location test.FIG. 126B is a bar graph demonstrating improvements in memory and/ordiscrimination in accordance with some embodiments.

FIG. 127A is a plot depicting the average amount of time the subjectsspent finding the hidden platform in the Morris water maze test on eachday. FIG. 127B is a bar graph depicting the average amount of time thesubjects spent searching for the removed platform in the target quadrantduring a probe test.

FIG. 128A is a series of representative immunofluorescence imagesillustrating enlarged vasculature in the visual cortex in accordancewith some embodiments. FIG. 128B is a bar graph depicting blood vesseldiameter in the visual cortex and illustrating an increase in bloodvessel diameter following gamma exposure in accordance with someembodiments.

DETAILED DESCRIPTION

In one aspect, the present disclosure provides methods, devices, andsystems for preventing, mitigating, and/or treating a brain disorder orcognitive dysfunction/deficit in a subject. In some embodiments, thebrain disorder is a dementia.

Cognitive function critically depends on the precise timing ofoscillations in neural network activity, specifically in the gammafrequency, a rhythm (e.g., about 20 Hz to about 100 Hz, about 20 Hz toabout 80 Hz, or about 20 Hz to about 50 Hz) linked to attention andworking memory. Because these oscillations emerge from synapticactivity, they provide a direct link between the molecular properties ofneurons and higher level, coherent brain activity. Importantly, gammaoscillatory activity is disrupted in neural circuits compromised bymolecular neuropathology in AD and may represent a key determinant ofmemory impairment in the disease. It has yet to be determined whetherthere is a causal relationship between pathology and impairment of brainoscillations. However, driving brain rhythms can serve as a multi-targettherapy for the treatment of a dementia, such as AD, and can be achievedvia non-invasive therapies.

In one aspect, the present disclosure provides devices, methods, andsystems for enhancing or inducing gamma oscillations. In someembodiments, the enhancement or induction of gamma oscillations is byoptogenetic methods. In other embodiments, the enhancement or inductionof gamma oscillations is by behavioral methods. The present disclosureprovides that the enhancement and/or induction of gamma oscillations byoptogenetic, behavioral, or other methods reduces AD pathology.

In one aspect, the present disclosure provides devices, systems, andmethods for restoration or induction of the gamma oscillatory rhythms insubjects having dementia. In some embodiments, the dementia is AD,vascular dementia, frontal temporal dementia (FTD), and/or Lewy Bodydementia. Thus, in some embodiments, the present disclosure providesdevices, systems, and methods for treating dementia.

As used herein, the terms “treatment” or “treating” refers to boththerapeutic treatment and prophylactic or preventive measures. In someembodiments, subjects in need of treatment include those subjects thatalready have the disease or condition as well as those subjects that maydevelop the disease or condition and in whom the object is to prevent,delay, or diminish the disease or condition. For example, in someembodiments, the devices, methods, and systems disclosed herein may beemployed to prevent, delay, or diminish a disease or condition to whichthe subject is genetically predisposed, such as AD. In some embodiments,the devices, methods, and systems disclosed herein may be employed totreat, mitigate, reduce the symptoms of, and/or delay the progression ofa disease or condition with which the subject has already beendiagnosed, such as AD.

As used herein, the term “subject” denotes a mammal, such as a rodent, afeline, a canine, or a primate. Preferably, a subject according to theinvention is a human.

The term “about,” as used herein, refers to plus or minus ten percent ofthe object that “about” modifies.

Dementias are disorders characterized by loss of intellectual abilitiesand/or memory impairments. Dementias include, for example, AD, vasculardementia, Lewy body dementia, Pick's disease, fronto-temporal dementia(FTD), AIDS dementia, age-related cognitive impairments, and age-relatedmemory impairments. Dementias may also be associated with neurologicand/or psychiatric conditions such, as, for example, brain tumors, brainlesions, epilepsy, multiple sclerosis, Down's syndrome, Rett's syndrome,progressive supranuclear palsy, frontal lobe syndrome, schizophrenia,and traumatic brain injury.

AD is the most frequent neurodegenerative disease in developedcountries. AD is histopathologically characterized by the accumulationof amyloid plaques comprised of the Aβ peptide and NFTs made of the tauprotein. Clinically, AD is associated with progressive cognitiveimpairment characterized by loss of memory, function, languageabilities, judgment, and executive functioning. AD often leads to severebehavioral symptoms in its later stages.

Vascular dementia can also be referred to as cerebrovascular dementiaand refers to cerebrovascular diseases (e.g., infarctions of thecerebral hemispheres), which generally have a fluctuating course withperiods of improvement and stepwise deterioration. Vascular dementia caninclude one or more symptoms of disorientation, impaired memory and/orimpaired judgment. Vascular dementia can be caused by discrete multipleinfarctions, or other vascular causes including, for example, autoimmunevasculitis, such as that found in systemic lupus erythematosus;infectious vasculitis, such as Lyme's disease; recurrent intracerebralhemorrhages; and/or strokes.

Frontal temporal dementia (FTD) is a progressive neurodegenerativedisorder. Subjects with FTD generally exhibit prominent behavioral andpersonality changes, often accompanied by language impairment.

Lewy body dementia is characterized by one or more symptoms of thedevelopment of dementia with features overlapping those of AD;development of features of Parkinson's disease; and/or early developmentof hallucinations. Lewy body dementia is generally characterized byday-to-day fluctuations in the severity of the symptoms.

In some aspects, the present disclosure provides methods for preventing,mitigating, and/or treating dementia in a subject, comprising inducingsynchronized gamma oscillations in the brain of the subject. In someembodiments, the induction of gamma oscillations in the subjectsuffering from a neurological disease or disorder or age-related declineacts to restore gamma oscillatory rhythms that are disrupted in thesubject as a result of or in association with the disease or disorder orage-related decline.

In some embodiments, the induction of gamma oscillations reducesgeneration of isoforms Aβ₁₋₄₀ and Aβ₁₋₄₂. In some embodiments, theinduction of gamma oscillations enhances clearance of Aβ (e.g., isoformsAβ₁₋₄₀ and Aβ₁₋₄₂) from the brain of the subject. In some embodiments,the induction of gamma oscillations prevents accumulation of Aβ in thebrain of the subject. In some embodiments, the methods provided hereinreduce the level of Aβ in the brain of the subject by about 10%, about20%, about 30%, about 40%, about 50%, about 60%, about 70%, or more,relative to the level of Aβ in the brain of the subject prior totreatment. In some embodiments, the level of Aβ in the brain of thesubject is reduced by at least about 50% relative to the level of Aβ inthe brain of the subject prior to treatment.

In some embodiments, the level of Aβ in the brain of the subject isreduced via reduction in the cleavage of APP in the brain of thesubject. In some embodiments, the methods provided herein reduce thecleavage of APP in the brain of the subject by about 10%, about 20%,about 30%, about 40%, about 50%, about 60%, about 70%, or more, relativeto the level of APP cleavage in the brain of the subject prior totreatment. In some embodiments, the level of APP cleavage in the brainof the subject is reduced by at least about 50% relative to the level ofAPP cleavage in the brain of the subject prior to treatment. In someembodiments, the level of APP cleavage is measured by the level ofC-terminal fragment β (β-CTF) in the brain of the subject. In someembodiments, the level of APP cleavage in the brain is reduced viainhibition of β- and/or γ-secretases, such as by increasing the level ofinhibition of β- and/or γ-secretase activity. In some embodiments, themethods provided herein reduce the aggregation of Aβ plaques in thebrain of the subject.

In some embodiments, the methods improve cognitive ability and/or memoryin the subject.

In another aspect, the present disclosure provides methods for inducinga neuroprotective profile or neuroprotective environment in the brain ofa subject, comprising inducing synchronized gamma oscillations in thebrain of the subject. For example, in some embodiments, theneuroprotective profile is associated with a neuroprotective microglialcell profile. In further embodiments, the neuroprotective profile isinduced by or associated with an increase in activity of the M-CSFpathway. In some embodiments, the neuroprotective environment isassociated with anti-inflammatory signaling pathways. For example, insome embodiments, the anti-inflammatory signaling pathways areanti-inflammatory microglia signaling pathways.

In some embodiments, the neuroprotective profile is associated with areduction in or a lack of pro-inflammatory glial cell activity.Pro-inflammatory glial cell activity is associated with an M1 phenotypein microglia, and includes production of reactive species of oxygen(ROS), neurosecretory protein Chromogranin A, secretory cofactorcystatin C, NADPH oxidase, nitric oxide synthase enzymes such as iNOS,NF-κB-dependent inflammatory response proteins, and pro-inflammatorycytokines and chemokines (e.g., TNF, IL-1β, IL-6, and IFNγ).

In contrast, an M2 phenotype of microglia is associated withdownregulation of inflammation and repair of inflammation-induceddamage. Anti-inflammatory cytokines and chemokines (IL-4, IL-13, IL-10,and/or TGFβ) as well as an increase in phagocytic activity areassociated with an M2 phenotype. Thus, in some embodiments, the methodsprovided herein elicit a neuroprotective M2 phenotype in microglia. Insome embodiments, the methods provided herein increase the phagocyticactivity in the brain of the subject. For example, in some embodiments,the methods provided herein increase phagocytic activity of microgliasuch that the clearance of Aβ is increased.

Gamma oscillations may include about 20 Hz to about 100 Hz. Thus, insome embodiments, the present disclosure provides methods forpreventing, mitigating, or treating dementia in a subject comprisinginducing gamma oscillations of about 20 Hz to about 100 Hz, or about 20Hz to about 80 Hz, or about 20 Hz to about 50 Hz, or about 30 to about60 Hz, or about 35 Hz to about 45 Hz, or about 40 Hz, in the brain ofthe subject. Preferably, the gamma oscillations are about 40 Hz.

A stimulus may include any detectable change in the internal or externalenvironment of the subject that directly or ultimately induces gammaoscillations in at least one brain region. For example, a stimulus maybe designed to stimulate electromagnetic radiation receptors (e.g.,photoreceptors, infrared receptors, and/or ultraviolet receptors),mechanoreceptors (e.g., mechanical stress and/or strain), nociceptors(i.e., pain), sound receptors, electroreceptors (e.g., electric fields),magnetoreceptors (e.g., magnetic fields), hydroreceptors,chemoreceptors, thermoreceptors, osmoreceptors, and/or proprioceptors(i.e., sense of position). The absolute threshold or the minimum amountof sensation needed to elicit a response from receptors may vary basedon the type of stimulus and the subject. In some embodiments, a stimulusis adapted based on individual sensitivity.

In some embodiments, gamma oscillations are induced in a brain regionspecific manner. For example, in some embodiments, the gammaoscillations are induced in the hippocampus, the visual cortex, thebarrel cortex, the auditory cortex, or any combination thereof. By wayof example, in some embodiments, the gamma oscillations are induced inthe visual cortex using a flashing light; and in other embodiments, thegamma oscillations are induced in the auditory cortex using auditorystimulation at particular frequencies. In some embodiments, the gammaoscillations are induced in multiple brain regions simultaneously usinga combination of visual, auditory, and/or other stimulations. In someembodiments, the gamma oscillations are induced in a virtual realitysystem.

In some embodiments, the subject receives a stimulus via an environmentconfigured to induce gamma oscillations, such as a chamber thatpassively or actively blocks unrelated stimuli (e.g., light blocking ornoise canceling). Alternatively or in addition, the subject may receivea stimulus via a system that includes, for example, light blocking ornoise canceling aspects. In some embodiments, the subject receives avisual stimulus via a stimulus-emitting device, such as eyewear designedto deliver the stimulus. The device may block out other light. In someembodiments, the subject receives an auditory stimulus via astimulus-emitting device, such as headphones designed to deliver thestimulus. The device may cancel out other noise.

In addition to at least one interface for emitting a stimulus, someembodiments may include at least one processor (to, e.g., generate astimulus, control emission of the stimulus, monitor emission of thestimulus/results, and/or process feedback regarding thestimulus/results), at least one memory (to store, e.g.,processor-executable instructions, at least one stimulus, a stimulusgeneration policy, feedback, and/or results), at least one communicationinterface (to communicate with, e.g., the subject, a healthcareprovider, a caretaker, a clinical research investigator, a database, amonitoring application, etc.), and/or a detection device (to detect andprovide feedback regarding, e.g., the stimulus and/or the subject,including whether gamma oscillations are induced, subject sensitivity,cognitive function, physical or chemical changes, stress, safety, etc.).

In some embodiments, the gamma oscillations are induced by a visualstimulus such as a flashing light at about 20 Hz to about 100 Hz. Inparticular embodiments, the gamma oscillations are induced by flashinglight at about 20 Hz to about 50 Hz. In further embodiments, the gammaoscillations are induced by flashing light at about 35 Hz to about 45Hz. In yet further embodiments, the gamma oscillations are induced byflashing light at about 40 Hz. In some embodiments, the subject receives(e.g., is placed in a chamber with or wears a light blocking deviceemitting) about 20 Hz to about 100 Hz flashing light, or about 20 Hz toabout 50 Hz flashing light or about 35 Hz to about 45 Hz flashing light,or about 40 Hz flashing light.

In some embodiments, the gamma oscillations are induced by an auditorystimulus such as a sound at a frequency of about 20 Hz to about 100 Hz,or about 20 Hz to about 80 Hz, or about 20 Hz to about 50 Hz, or about35 Hz to about 45 Hz, or about 40 Hz. In some embodiments, the subjectreceives (e.g., is placed in a chamber with or wears a noise cancelingdevice emitting) an auditory stimulus of about 20 Hz to about 100 Hz,about 20 Hz to about 80 Hz, about 20 Hz to about 50 Hz, about 35 Hz toabout 45 Hz, or about 40 Hz.

In some embodiments, the subject receives (e.g., is placed in a chamberwith or wears a light blocking device emitting) the visual and/orauditory stimuli for about one hour, about 2 hours, about 3 hours, about4 hours, about 5 hours, or more. In some embodiments, the subjectreceives (e.g., is placed in a chamber with or wears a light blockingdevice emitting) the stimuli for no more than about 6 hours, no morethan about 5 hours, no more than about 4 hours, no more than about 3hours, no more than about 2 hours, or no more than about one hour. Insome embodiments, the subject receives (e.g., is placed in a chamberwith or wears a light blocking device emitting) the stimuli for lessthan an hour.

In some embodiments, the subject undergoes with the methods providedherein. In other embodiments, the subject undergoes treatment with themethods provided herein on multiple separate occasions. Subjects may betreated on a regular schedule or as symptoms arise or worsen. In someembodiments, chronic treatment may be effective at reducing soluble Aβpeptide and/or insoluble Aβ peptide (i.e., plaques).

In some embodiments, the gamma oscillations are induced in a cell-typespecific manner. In some embodiments, the gamma oscillations are inducedin FS-PV-interneurons. The term “fast-spiking” (FS) when used todescribe a class of neurons refers to the capacity of the neurons todischarge at high rates for long periods with little spike frequencyadaptation or attenuation in spike height. Thus, these neurons arecapable of sustained high frequency (e.g., equal to or greater thanabout 100 Hz or about 150 Hz) discharge without significantaccommodation. This property of FS neurons is attributable in largemeasure to their expression of fast delayed rectifier channels, in otherwords, channels that activate and deactivate very quickly.

In one aspect, the stimulations may be non-invasive. The term“non-invasive,” as used herein, refers to devices, methods, and systemswhich do not require surgical intervention or manipulations of the bodysuch as injection or implantation of a composition or a device. Forexample, the stimulations may visual (e.g., flickering light), audio(e.g., sound vibrations), and/or haptic (mechanical stimulation withforces, vibrations, or motions).

In another aspect, the stimulations may be invasive or at leastpartially invasive. For example, visual, audio, and/or hapticstimulations may be combined with an injection or implantation of acomposition (e.g., a light-sensitive protein) or a device (e.g., anintegrated fiber optic and solid-state light source).

EXPERIMENTAL DATA

Gamma Oscillations are Decreased During Hippocampal SWR in 5×FAD MiceEarly in Disease.

Deficits in gamma have been observed in multiple brain regions inseveral neurological and psychiatric disorders including a reduction inspontaneous gamma synchronization in human patients with AD.Intriguingly, reduced spontaneous gamma has also been found in two mousemodels of AD (a human amyloid precursor protein (hAPP) Tg mouse and anApolipoprotein E4 allele (APOE4) knock-in mouse) in vivo and in in vitroslice studies in another mouse model (Tg CRND8 mouse). However, it isunclear if gamma oscillations are altered in other mouse models of AD,if it occurs early in disease progression, and if gamma disruptionaffects disease progression.

To address these questions, neural activity from awake behaving 5×FADmice, a well-established model of AD that carries five familial ADmutations was recorded. In particular, 5×FAD mice express five differentalleles of familial AD including APP KM670/671NL (Swedish), APP 1716V(Florida), APP V717I (London), PSEN1 M146L (A&gt;C), and PSEN1 L286V.Thus, 5×FAD mice were used as a model of AD amyloid pathology. In someembodiments, the neural activity is recorded from the mice atapproximately 3 months of age, when they have elevated levels of Aβ, butbefore the onset of major plaque accumulation and manifestation oflearning and memory deficits. FIG. 1 is a schematic diagram illustratinga mouse running through a virtual linear maze on a spherical treadmillin accordance with some embodiments. Food-restricted mice may receivereward for running back and forth through a virtual linear maze on aspherical treadmill.

Neural activity from hippocampal subregion CA1 may be recorded. FIGS. 2Aand 2B are electrical traces recorded from hippocampal CA1 andillustrating theta oscillations and sharp-wave ripples (SWRs) inaccordance with some embodiments. In some embodiments, gammaoscillations in CA1 may be present during distinct periods of activitysuch as, during running, when theta oscillations (4-12 Hz) are observed,as illustrated in FIG. 2A, and during quiescent and exploratorybehavior, when SWRs occur, as illustrated in FIG. 2B.

Power spectral densities during theta oscillations were examined and noclear differences were found in slow gamma power (20 Hz to 50 Hz range)between 5×FAD mice and WT littermates. FIGS. 3A and 3B are plotsillustrating the mean and standard deviation of normalized powerspectrum and normalized power spectral densities during theta periods inthree-month-old Tg 5×FAD and WT mice in accordance with someembodiments. FIG. 3A illustrates the mean and standard deviation of thenormalized power spectrum during theta periods in three-month-old 5×FAD(n=6 mice) and WT (n=6 mice) mice. In some embodiments, each animal'spower spectral density may be normalized to its peak (in theta). FIG. 3Billustrates the normalized power spectral densities during theta periodsin three-month-old 5×FAD (n=6 mice) and WT (n=6 mice) mice.

As a next step, in some embodiments, gamma oscillations during SWRs,high frequency oscillations of 150-250 Hz that last around 50-100 mswere examined. SWRs are associated with bursts of population activityduring which patterns of spiking activity are replayed across thehippocampus. Prior work has shown that slow gamma is elevated duringSWRs and synchronized across CA3 and CA1. As a result, neurons acrossthese hippocampal subregions are more likely to fire together duringSWRs because neurons are more likely to fire phase locked to gamma. Astudy was conducted in which SWRs (defined as periods when power in theripple band, about 150 Hz to about 250 Hz, exceeded four standarddeviations above the mean) were identified and spectrograms were plottedto examine power across a range of frequencies during these SWRs. In thespectrograms, increased power above 100 Hz indicative of the highfrequency oscillations characteristic of SWRs, as well as increasedpower below approximately 50 Hz, indicative of a concurrent increase ingamma power may be observed.

FIGS. 4A and 4B are spectrograms illustrating SWRs for a WT mouse and a5×FAD mouse in accordance with some embodiments. FIG. 4A illustratesthat average SWR-triggered spectrograms for one WT mouse shows anincrease in the gamma band 402, during SWRs 404 with frequencies below80 Hz enlarged in the right plot. FIG. 4B illustrates that averageSWR-triggered spectrograms for one 5×FAD mouse shows an increase in thegamma band during SWRs though this increase is lower than in the WTmouse as illustrated in FIG. 4A.

In some embodiments, the study found that the instantaneous frequenciesof these slower oscillations (10-50 Hz range, as described furtherherein) were a unimodal distribution centered around 40 Hz. FIGS. 5A-5Care plots depicting the distribution of instantaneous gamma frequenciesduring SWRs in accordance with some embodiments. FIG. 5A illustrates thedistribution of instantaneous gamma frequencies during SWRs for the samemouse shown in FIG. 4A peak around 40 Hz (n=370 SWRs). FIG. 5Billustrates that the distribution of instantaneous gamma frequenciesduring SWRs in 5×FAD and WT mice show distributions around 40 Hz foreach recording session, and FIG. 5C illustrates the mean and standarderror of mean (SEM) across animals (n=820, 800, 679, 38, 1875, 57 gammacycles per session in six 5×FAD animals and 181, 1075, 919, 1622, 51,1860, 1903 gamma cycles session in six WT animals).

In some embodiments, these gamma oscillations during SWRs in WT micewere then compared to those in 5×FAD littermates and a deficit was foundin gamma during SWRs: while gamma power did increase from baselineduring SWRs in 5×FAD mice, gamma power during SWRs was significantlysmaller in 5×FAD than in WT mice, as described further herein.

FIG. 6A is a series of graphs depicting the z-scored gamma power as afunction of the time from the peak of the SWRs in 5×FAD and WT mice,respectively, in accordance with some embodiments. FIG. 6A shows meanand SEM, and illustrates gamma power increases during SWRs relative tobaseline.

FIG. 6B is a plot depicting the cumulative distribution of gamma powerduring SWRs in 5×FAD and WT mice in accordance with some embodiments.The cumulative distribution of gamma power during SWRs showssignificantly smaller increases in 5×FAD than WT mice (ranksum test,p<10⁻⁵; n=2166 SWRs in six 5×FAD mice and 3085 SWRs in six WT mice;z-score median 1.02 (0.39-1.87, 25^(th)-75^(th) percentiles) in 5×FADmice and z-score median 1.18 (0.53-2.15, 25^(th)-75^(th) percentiles) inWT mice).

FIGS. 6C and 6D are plots depicting the cumulative distribution of thez-scored gamma power during the 100 ms around the peak of the SWRs forWT mice 606 and 5×FAD mice 608 and the mean and SEM (shaded) acrossanimals (n=514, 358, 430, 22, 805, 37 SWRs per session in six 5×FADanimals and 82, 311, 370, 776, 18, 710, 818 SWRs per session in six WTanimals) in accordance with some embodiments.

FIG. 6E is a plot depicting the cumulative distribution of z-scoredgamma power during the 100 ms around the peaks of large SWRs (detectionthreshold greater than 6 standard deviations above the mean) in WT mice614 and 5×FAD mice 616 in accordance with some embodiments. Ranksumtests were performed throughout for data that was not normallydistributed, as described further herein. FIG. 6E shows significantlysmaller increases in WT mice 614 and 5×FAD mice 616 (ranksum test,p<10⁻⁵, n=1000 SWRs in six 5×FAD mice and 1467 SWRs in six WT mice).

In some embodiments, spiking was phase modulated by these gammaoscillations in both groups, however modulation of spiking by gammaphase was weaker in 5×FAD than in WT animals. The study found that thedepth of modulation may be significantly smaller in 5×FAD than in WTanimals.

FIG. 7A is a plot depicting fraction of spikes as function of phase ofgamma oscillation, and FIG. 7B is a plot depicting depth of modulationof spiking during SWRs as a function of gamma phase during SWRs inthree-month-old 5×FAD (n=6 mice) and WT (n=6 mice) mice in accordancewith some embodiments (ranksum test, bootstrap resampling, p<10⁻⁵, whichis significant when controlling for multiple comparisons, n=2500 5×FADspike-gamma phase distributions and 3000 WT distributions, depth ofmodulation median 0.35 (0.21-0.44, 25^(th)-75^(th) percentiles) in 5×FADmice and depth of modulation median 0.38 (0.29-0.47,25^(th)-75^(th)percentiles) in WT mice). Error bars indicate mean+/−SEM.Plot 704 illustrates histogram of the depth of modulation of spiking

FIGS. 7C and 7D are plots illustrating fraction of spikes in hippocampalCA1 during SWRs as a function of phase of gamma oscillations in 5×FADand WT animals for each animal and the mean and SEM across animals(n=2475, 1060, 3092, 25, 6521, 123 spikes during SWRs per session in six5×FAD animals and 360, 4741, 1564, 2961, 88, 3058, 4270 spikes duringSWRs per session in six WT animals) in accordance with some embodiments.

FIG. 7E is a plot depicting fraction of spikes as function of phase ofgamma oscillation, and FIG. 7F is a plot depicting depth of modulationof spiking during large SWRs (detection threshold greater than 6standard deviations above the mean, as described further herein) inthree-month-old 5×FAD (n=6 mice) and WT (n=6 mice) mice (ranksum test,bootstrap resampling one asterisk indicates p<10⁻¹⁰, n=2500 5×FADspike-gamma phase distributions and 3000 WT distributions) in accordancewith some embodiments. Error bars indicate mean+/−SEM.

The study also found that there may be fewer SWRs per time in non-thetaperiods in 5×FAD mice compared to WT (ranksum test, p<10⁻⁵, n=634non-theta periods in six 5×FAD mice and 750 non-theta periods in six WTmice, median 0.07 Hz (0-0.17, 25^(th)-75^(th) percentiles) in 5×FAD miceand median 0.12 Hz (0-0.24, 25^(th)-75^(th) percentiles) in WT mice),further reducing the periods when gamma power is elevated as disclosedabove).

FIGS. 8A and 8B are plots depicting SWR rate per non-theta period in5×FAD mice 802 and WT mice 804 animals for each animal (FIG. 8A) and allanimals combined (FIG. 8B) in accordance with some embodiments (ranksumtest, p<10⁻¹⁰, n=117, 210, 151, 55, 100, 1 non-theta periods per sessionin six 5×FAD animals and 80, 68, 115, 95, 15, 159, 218 non-theta periodsper session in six WT animals). These results reveal deficits in gammaoscillations and modulation of hippocampal CA1 spiking in a mouse modelof AD prior to development of major amyloid plaque accumulation andevidence of cognitive deficits.

Optogenetic Stimulation of FS-PV-Interneurons at Gamma Frequency DroveGamma Oscillations in the CA1 Region of the Hippocampus.

The observation of gamma deficits during SWRs early in the progressionof the disease in this mouse model of AD prompts the question of whethergamma oscillations could affect molecular and cellular ADpathophysiology. To test that, gamma oscillations were optogeneticallydriven by expressing ChR2 in a Cre-dependent manner using adouble-floxed inverted open reading frame (DIO) ChR2-EYFPadeno-associated virus (AAV) in FS-PV-interneurons in hippocampal CA1 of2.5-month-old 5×FAD/PV-Cre bi-transgenic mice. A study was conducted todetermine if genetic induction of hippocampal gamma oscillations in miceaffects molecular pathology in a mouse model of AD. Hippocampal gammaoscillations were genetically induced in awake, behaving WT and 5×FADmice.

An adeno-associated virus (i.e., an AAV5 virus) with a double-floxed,inverted, open-reading-frame (DIO) ChR2 coupled to enhanced yellowfluorescent protein (EYFP) driven by the EF1α promoter was generated.FIG. 9 is a schematic diagram illustrating a viral vector (i.e.,AAV5-DIO-ChR2-EYFP) for regulating activation of a specific cell type inthe brain of a subject in accordance with some embodiments. Viralexpression was targeted to the CA1 region of the hippocampus in acell-type-specific manner. In the presence of Cre-recombinase, one oftwo incompatible loxP variants flips to allow expression of ChR2.

The CA1 region of the hippocampuses of 5×FAD mice were infected witheither the AAV-DIO-ChR2-EYFP or an EYFp-only construct using astereotaxic viral injection method allowing precise regional targetingof viral infection. In one embodiment, at the time of injection, aferrule containing a fiber optic cable (white bar) was placed about 0.3mm above the targeted brain region. After two weeks, which provided timefor the mice to recover and the virus to express in the PV cells, CA1interneurons were optogenetically manipulated.

FIGS. 10A and 10B are schematic diagrams illustrating delivery of asignal to the CA1 region of the hippocampus of a subject in accordancewith some embodiments. In FIG. 10A, a mouse is shown running on a ballthrough a maze while undergoing gamma stimulation via optogenetics inthe hippocampus in accordance with some embodiments. As shown in FIGS.10A and 10B, arrow 1000 indicates the blue light that flickers at about40 Hz to activate the brain region.

In the example, a 200-mW 493-nm DPSS laser was connected to a patch cordwith a fiber channel/physical contact connector at each end. During theexperiment, about 1 mW of optical stimulation was delivered for aboutone hour. More specifically, blue light (e.g., 473 nm) was delivered atvarious frequencies, including theta (e.g., about 8 Hz), gamma (e.g.,about 40 Hz), and also randomly at about 40 Hz through an optical fiberpositioned just above the CA1 region of the hippocampus. In someembodiments, no stimulation conditions were tested. The theta conditionserved as a frequency control, and the random condition controlled forrhythmicity specificity in accordance with some embodiments.

Following the completion of the one-hour stimulation, brain tissue wasdissected and frozen at −80° C. for staining and enzyme-linkedimmunosorbent assay (ELISA) analyses. FIG. 11 is an immunofluorescenceimage illustrating immunostaining of neural tissue in a subject withChR2 and DAPI in accordance with some embodiments. In the example, FIG.11 shows the DAPI (nuclei) and ChR2 staining in the hippocampus.

FIG. 12A is an immunofluorescence image illustrating ChR2-EYFP expressedin PV+ interneurons in accordance with some embodiments. FIG. 12A showsChR2-EYFP was strongly expressed in PV+ interneurons in CA1 ofthree-month-old 5×FAD/PV-Cre mice (scale bar=100 μm). FIG. 12B is aseries of immunofluorescence images illustrating immunohistochemistrywith anti-EYFP and anti-PV antibodies in three-month-old 5×FAD/PV-CreCA1 expressing AAV DIO ChR2-EYFP that shows EYFP expression only in PV+cells (scale bar=50 μm). To compare 5×FAD and WT mice, ChR2 wasexpressed in FS-PV-interneurons in 5×FAD-negative littermates. As acontrol for the non-specific effects of light stimulation, 5×FAD/PV-Crebi-transgenic mice expressing AAV-DIO, which contained EYFP only wasused. In these mice, with an identical genetic background and lightdelivery conditions, light delivery does not result in optogeneticstimulation. In some embodiments, the FS-PV-interneurons at 40 Hz werechosen for two reasons. First, previous studies have shown that drivingFS-PV-interneurons at 40 Hz produced the largest LFP responses. Second,in some embodiments, deficits in gamma during SWRs was found, andinstantaneous gamma frequencies during SWRs formed a distributioncentered around 40 Hz as illustrated in FIGS. 5A-5C. In someembodiments, for electrophysiological recordings, periods of 40-Hzstimulation were interleaved with periods of no stimulation or periodswith stimulation delivered at a randomized interval selected from aPoisson distribution centered at 40 Hz as described further herein.

FIGS. 13A and 13B include a schematic diagram of a study, an electricaltrace of a local field potential, and power spectral density ofFS-PV-interneurons in accordance with some embodiments. Referring toFIG. 13A, 1302 is an electrical trace of a local field potential in CA1before and during 40 Hz optogenetic drive of FS-PV-interneurons. Plot1304 illustrates the mean and standard deviation of power spectraldensity during 40-Hz stimulation, random stimulation (stimulation with arandomized interval selected from a Poisson distribution centered at 40Hz), or no stimulation of FS-PV-interneurons in CA1 (n=four 5×FAD andthree WT mice). FIG. 13B illustrates power spectral density during 40-Hzstimulation 1306, random stimulation 1308, or no stimulation 1310 ofFS-PV-interneurons in CA1 for each mouse (n=four 5×FAD mice with 169,130, 240, 73 40 Hz, 143, 129, 150, 72 random, and 278, 380, 52, 215 nostimulation periods per animal; and n=three WT mice with 65, 93, 91 40Hz, 64, 93, 90 random, and 187, 276, 270 no stimulation periods peranimal). Delivering 1 ms of 473-nm-light pulses at 40 Hz resulted inincreased power at 40 Hz in the LFPs as illustrated in FIG. 13A and inplot 1306 of FIG. 13B, while random stimulation did not result inincreased power at 40-Hz, as illustrated in FIG. 13A and in plot 1308 ofFIG. 13B.

Furthermore, in some embodiments, light pulses effectively drove spikes2-3 ms after light onset, and spikes per pulse were similar in bothrandom and 40-Hz conditions. FIGS. 14A and 14B include a raw electricaltrace, the trace filtered for spikes after optogenetic stimulation, andplots of spike probability after the onset of 1 ms laser pulse inaccordance with some embodiments. FIG. 14A illustrates an example rawtrace 1402 and the trace filtered for spikes (300-6000 Hz) 1404 afteroptogenetic stimulation 1406. Plot 1408 illustrates histogram of spikesper pulse after the onset of the 1 ms laser pulse during 40-Hzstimulation, random stimulation, or no stimulation (n=345762 40-Hzstimulation, 301559 random pulse stimulation, and 32350 no stimulationtimes at least 500 ms apart from 552 40-Hz stimulation, 543 randomstimulation, and 1681 no stimulation periods in four 5×FAD and three WTmice). FIG. 14B shows spike probability after the onset of the 1 mslaser pulse in response to 40-Hz stimulation 1412, random stimulation1414, or no stimulation 1410 with an increase in spiking around 2-3 msafter the laser pulse onset (n=four 5×FAD with 87, 130, 8, 73 40-Hzstimulation, 85, 129, 5, 72 random stimulation, and 251, 379, 15, 215 nostimulation periods per animal; and n=three WT with 65, 93, 91 40-Hzstimulation periods per animal, 64, 93, 90 random stimulation periodsper animal, and 187, 277, 270 no stimulation periods per animal). Errorbars show mean+/−SEM.

Thus, 40-Hz oscillations in CA1 were effectively driven via optogeneticstimulation of FS-PV-interneurons. Previous studies have shown that Aβpeptide levels were elevated following increases in neural activity andreduced following silencing of neural activity. In some embodiments, therandom stimulation condition was used to control for overall changes inspiking activity caused by stimulation. In some embodiments, multi-unitfiring rates were compared during interleaved periods of 40 Hz andrandom stimulation and no significant differences were found betweenfiring rates in these conditions.

FIG. 15A is a histogram illustrating the difference in firing ratesbetween 40-Hz stimulation and random stimulation periods in accordancewith some embodiments. FIG. 15A shows that both types of stimulationelicit similar amount of spiking activity (Wilcoxon signed rank test forzero median, p>0.6, n=538 stimulation periods from four 5×FAD and threeWT mice, “n.s.” indicates not significant). Wilcoxon signed rank testfor zero median of the distribution of differences between firing ratesduring 40 Hz and random stimulation for all mice together p>0.6: median−1.75×10⁻⁵ Hz (−1.28-1.18 Hz, 25^(th)-75^(th) percentiles) n=538stimulation periods.

FIG. 15B is a bar graph illustrating multiunit firing rates per 40-Hzstimulation 1512, random stimulation 1514, and no stimulation 1510periods for each animal (ranksum tests for each animal, three WT andfour 5×FAD mice, p>0.09, median and quartiles shown in figure, n=87,130, 8, 65, 93, 91, 73 40-Hz stimulation periods and 85, 129, 5, 64, 93,90, 72 random stimulation periods per mouse). Box and whisker plots showmedian (white lines in box) and quartiles (top and bottom of box). Inall animals firing rates between 40 Hz and random stimulation were notsignificantly different showing that the random stimulation conditionserves as a control for spiking activity (ranksum tests for each animal,three WT and four 5×FAD mice, p>0.09, median and quartiles shown infigure, n=87, 130, 8, 65, 93, 91, 73 40-Hz stimulation periods and 85,129, 5, 64, 93, 90, 72 random stimulation periods per animal). Whether40-Hz stimulation caused neuronal hyperactivity relative to nostimulation was also examined. In most animals the firing rates between40 Hz or random stimulation and no stimulation were not significantlydifferent (ranksum tests for each animal, 2 WT and two 5×FAD, p>0.25,n=8, 93, 91, 73 40-Hz stimulation periods and 15, 277, 270, 215 baselineperiods per animal) or the firing rates during 40-Hz or randomstimulation were lower than during no stimulation (ranksum tests foreach animal, 1 WT and 1 5×FAD, p<10⁻⁵, which is significant, whencorrected for performing multiple comparisons, n=130, 65 40-Hzstimulation periods and 379, 187 baseline periods per animal) indicatingthat 40-Hz stimulation did not cause neuronal hyperactivity. In oneanimal there was significantly more activity with 40 Hz or randomstimulation than during baseline (ranksum test for 1 5×FAD, mouse,p<10⁻⁵, n=87 40-Hz stimulation periods and 251 baseline periods peranimal). Therefore in six out of seven animals there is no evidence thatthe 40 Hz optogenetic stimulation of FS-PV-interneurons causeshyperactivity. Therefore, in some embodiments while the random conditiondid not induce gamma oscillations, it did result in similar amounts ofmulti-unit spiking activity as illustrated in FIG. 15A.

FIG. 16A is an electrical trace recorded from a hippocampus of a subjectduring a frequency-specific increase in the stimulation of a specificcell type in the CA1 region of the hippocampus of a subject inaccordance with some embodiments. More specifically, FIG. 16A wasrecorded from the hippocampus of a subject during the frequency-specificincrease in the stimulation of the FS-PV+(i.e., the gamma condition) inaccordance with some embodiments.

FIG. 16B is a plot of power spectral density illustrating afrequency-specific increase in the local field potential power in thestimulation of a specific cell type in the CA1 region of the hippocampusof a subject in accordance with some embodiments. In particular, thepower spectral density graph in FIG. 16B verifies the specificity of thestimulation. Local field potential (LFP) power was enhanced only in the40 Hz band 1600 during the gamma stimulation condition when the FS-PV+are activated by 40-Hz blue light pulses (n=4 mice per group). Neitherbaseline nor random stimulation conditions showed enhancement at thisfrequency 1600.

Gamma Stimulation Reduced Aβ Production in the CA1 Region of theHippocampus.

Accumulation of Aβ may initiate multiple neurotoxic events typical forAD pathology. Therefore, in some embodiments, gamma stimulation affectsin overall Aβ peptide levels in 5×FAD mice were examined. Mice that werethree months old were used because plaques are not present in thehippocampus at this stage in these mice, allowing soluble Aβ dynamicsindependent of plaque load to be investigated. In some embodiments, itwas found that one hour of stimulation of FS-PV-interneurons reducedAβ₁₋₄₀ by 53.22% and Aβ₁₋₄₂ by 44.62% in the 40 Hz group compared to theEYFP control group in the CA1 region of the hippocampus, as measured byAβ ELISA analyses.

FIGS. 17A and 17B are bar graphs depicting relative Aβ₁₋₄₀ and Aβ₁₋₄₂levels of 5×FAD/PV-Cre CA1 by one-way ANOVA grouping all mice togetherin accordance with some embodiments (n=8 EYFP mice and 740 Hz mice forAβ₁₋₄₀, n=4 mice per group for Aβ₁₋₄₂). The bar graph in FIG. 17Arepresents relative Aβ₁₋₄₀ levels of 5×FAD/PV-Cre CA1 in eachstimulation condition. Circles 1702 superimposed on bars in bar graphsindicate individual data points in each group (n=8 EYFP, n=7 40-Hz, n=48-Hz, n=6 random 5×FAD/PV-Cre mice per group). Notation “n.s.” 1704indicates not significant, asterisk 1706 indicates p<0.05, doubleasterisks 1708 indicate p<0.01 by one-way ANOVA for all bar graphs inthis figure. FIG. 17B represent relative Aβ₁₋₄₂ levels of 5×FAD/PV-CreCA1 in each simulation condition (n=4 EYFP, n=4 40-Hz, n=3 8 Hz n=3random 5×FAD/PV-Cre mice per group). FIGS. 17A and 17B show mean andSEM.

TABLE 1 (below) depicts significantly different p<0.05 by Student'st-test, raw concentration (pg/ml) values when mice from the same litterthat receive different conditions are compared. TABLE 1 displays rawAβ₁₋₄₀ and Aβ₁₋₄₂ levels with ELISA dilution for each experimentalgroup.

TABLE 1 Dilution Average Aβ₁₋₄₀ Average Aβ₁₋₄₂ Treatment FactorConcentration (pg/ml) Concentration (pg/ml) Optogenetics PV-Cre EYFP 1:2100.01, 61.598, 65.462, 58.777, 54.546, 30.585 82.509, 69.023, 70.831,82.152, 74.314 PV-Cre 40 Hz 1:2 46.604, 31.041, 26.639, 27.271, 41.950,18.790, 55.612, 69.326, 17.711, 18.262 3.9951 PV-Cre 8 Hz 1:2 101.268,54.283, 90.190, 50.699, 122.85, 35.507 151.690 PV-Cre Random 1:2 235.68,89.962, 157.37, 54.029, 137.78, 144.63 323.902, 451.78, 241.63αCaMKII-Cre EYFP 1:2 45.813, 59.069, 40.404, 72.052, 36.573, 67.243,66.810 59.295 αCaMKII-Cre 40 Hz 1:2 55.942, 44.270, 57.498, 70.847,79.683, 61.429 47.382, 115.08, 75.673 αCaMKII-Cre 8 Hz 1:2 52.829,46.604, 57.720 95.939, 21.640, 102.987 αCaMKII-Cre Random 1:2 218.00,191.72, 159.07 66.203, 168.867, 176.404 Light Flicker Dark one hour VC1:2 343.8, 245.3, 210.6, 343.8, 449.5, 320.7, 275.2, 588.4, 394.9,151.5, 334.4, 449.5, 769.2, 516.2 301.1, 185.6 Light one hour VC 1:2366.9, 632.4, 378.2, 314.1, 616.4, 592.3, 802.9, 266.9, 264.1 394.5,330.7, 337.8 20 Hz one hour VC 1:2 944.4, 313.2, 595.9, 530.9, 1624,302.4, 816.9, 687.2, 456.5, 289.9 676.6, 343.0 40 Hz one hour VC 1:2146.4, 143.6, 104.9, 99.6, 191.4, 187.7, 137.2, 179.7, 219.8, 100.4,98.46, 130.2, 234.9, 287.3 71.96, 68.31, 123.3, 150.7 80 Hz one hour VC1:2 332.5, 328.7, 363.5, 390.6, 558.3, 418.9, 510.7, 530.0, 673.3 609.5,1186, 921.9 40 Hz + PTX one hour 1:2 367.2, 431.4, 445.2, 392.4, 396.6,540.5, 532.7, VC 386.7, 445.2 705.0, 104.5, 104.5 Random one hour VC 1:2461.8, 100.2, 9.819, 416.6 423.9, 157.9, 389.9, 841.5 Dark one hour HPC1:2 97.949, 107.33, 119.92, 499.30, 355.13, 469.53, 139.33 598.03 40 Hzone hour HPC 1:2 88.136, 104.78, 161.52, 364.53, 408.41, 436.62, 197.36873.83 Random one hour HPC 1:2 95.816, 136.77, 70.004, 466.39, 500.87,311.26, 125.47 582.355 Dark seven days soluble  1:50 1216.9, 1181.3,1173.4, 5217.2, 8057.9, 9051.3, 1199.5, 134.73, 151.34, 6773.7, 244.11,236.96, 113.26, 145.14, 127.91, 235.38, 240.62, 286.19, 127.48, 143.02,127.48, 8.382, 11.21, 14.03, 13.56 141.07 Dark seven days  1:100 1173.2,1208.2, 1205.3, 8572.7, 9127.1, 6349.3, insoluble 1214.6, 994.86,1059.2, 10138, 6852.2, 7056.7, 1176.6, 1065.4, 1002.9, 7039.7, 7094.2,7289.0, 306.16, 690.70, 3442.7, 748.21, 1117.1, 1055.5, 152.73 504.95 40Hz seven days  1:50 476.71, 283.83, 336.87, 419.7, 248.1, 242.7, soluble237.22, 7.0175, 4.1480, 90.974, 95.626, 56.936, 4.0580, 1.5205, 91.864,67.577, 47.586, 200.87, 152.73, 148.84, 141.07, 13.56, 9.794, 15.44,3.677 162.44 40 Hz seven days  1:100 281.97, 270.37, 86.199, 202.96,130.71, 195.73, insoluble 239.71, 23.557, 15.166, 193.70, 1646.89,1579.1, 22.714, 1038.9, 1099.8, 503.44, 1400.0, 7536.62, 1760.8, 1558.8,187.69, 955.23, 1208.8, 694.57, 22.64 784.91 Dark one hour BC 1:281.874, 18.343, 86.554 391.95, 883.69, 604.97 40 Hz one hour BC 1:281.307, 27.986, 30.113 300.34, 1152.5, 616.92 40 Hz one hour wait 4 1:291.06, 141.8, 111.2, 12.30 108.0, 168.1, 157.3, hours 35.158 40 Hz onehour wait 12 1:2 167.2, 101.6, 89.31, 119.9 236.1, 134.6, 124.8, 152.4hours 40 Hz one hour wait 24 1:2 246.7, 177.6, 281.2, 175.0, 231.8,107.0, 402.7, hours 257.3, 204.2 184.6, 245.1, 179.7 Dark APP/PS1 1:21050.16, 1085.25, 1522.45, 19.22, 30.68, 28.08, 1153.69, 1750.77 14.25,25.30 40 Hz APP/PS1 1:2 512.42, 947.80, 850.45, 18.85, 15.58, 18.92,11.44 793.63 Dark WT 1:1 0.038, 0.813, 2.016, 1.913, N/A 0.313, 4.11,7.23, 20.2, 40.4, 38.7, 11.9 40 Hz WT 1:1 0.139, 0.325, 0.346, 0.390,N/A 8.92, 12.1, 6.34, 12.4, 13.1

In some embodiments, a comprehensive set of control experiments wereperformed to determine whether the effect was specific to frequency,cell-type, and/or rhythmicity. To determine frequency specificity,FS-PV-interneurons of the 5×FAD/PV-Cre bi-transgenic mice at 8 Hz weredriven and no change in Aβ levels was observed. Then, FS-PV-interneuronswere driven at random and the effect was specific to rhythmicstimulation. Indeed, amyloid levels were not reduced following randomstimulation, and in fact, Aβ₁₋₄₀ instead increased by 230.1% and Aβ₁₋₄₂by 133.8% (see, e.g., FIGS. 17A and 17B, p<0.01 by one-way ANOVAgrouping all mice together, n=8 EYFP mice and n=4 random mice forAβ₁₋₄₀, n=3 mice per group for Aβ₁₋₄₂. Mice from the same litter thatreceived different conditions were compared and significantly differentp<0.01 by Student's t-test were observed).

Finally, cell-type specificity of the effect by stimulating at 8 Hz and40 Hz in CamKII+ excitatory neurons in hippocampal CA1 using5×FAD/αCamKII-Cre bi-transgenic mice was tested. FIGS. 18A and 18B arebar graphs depicting relative Aβ₁₋₄₀ and Aβ₁₋₄₂ levels of5×FAD/αCamKII-Cre CA1 by one-way ANOVA in accordance with someembodiments. FIG. 18A represents relative Aβ₁₋₄₀ levels of5×FAD/αCamKII-Cre CA1 in each simulation condition. Circles 1802superimposed on bars in bar graphs indicate individual data points ineach group (n=6 40-Hz, n=3 8-Hz, n=3 random 5×FAD/αCamKII-Cre mice pergroup, notation “n.s.” 1804 indicates not significant, asterisks 1806indicate p<0.001 by one-way ANOVA).

FIG. 18B represents relative Aβ₁₋₄₂ levels of 5×FAD/αCamKII-Cre CA1 ineach simulation condition (n=3 αCamKII-Cre mice per group). In someembodiments, it was found that driving CamKII+ excitatory neurons at 8Hz or 40 Hz did not produce significant differences in Aβ₁₋₄₀ and Aβ₁₋₄₂levels (see, e.g., FIGS. 18A and 18B, right, p>0.05 by one-way ANOVA,n=6 40 Hz mice and 3 8 Hz mice (Aβ₁₋₄₀), n=3 mice per group (Aβ₁₋₄₂). Ifmice from the same litter that received different conditions arecompared, they are not significantly different p>0.05 by Student'st-test). Similarly to 5×FAD/PV-Cre mice, driving CamKII+ neurons withrandom stimulation also resulted in a 257.6% elevation of Aβ₁₋₄₀ and133.3% increase of Aβ₁₋₄₂ (see, e.g., FIGS. 18A and 18B, right, p<0.001by one-way ANOVA, n=5 40 Hz mice and 3 random mice for Aβ₁₋₄₀, n=3 miceper group for Aβ₁₋₄₂. If mice from the same litter that receiveddifferent conditions are compared then Aβ₁₋₄₀ is significantly differentp<0.001 by Student's t-test and Aβ₁₋₄₂, p=0.13 by Student's t-test).

Thus, the reduction of Aβ peptide levels following 40-Hz stimulation maybe specific to driving the FS-PV-interneurons. In some embodiments, toconfirm these ELISA findings with immunohistochemistry, Aβ-labeling wasperformed using a fl-amyloid C-terminal end-specific antibody that doesnot cross react with APP in CA1.

FIG. 19A is a series of images illustrating immunohistochemistry withanti-Aβ and anti-EEA1 antibodies in hippocampal CA1 region in accordancewith some embodiments. In particular, FIG. 19A is a series ofimmunofluorescence images illustrating immunohistochemistry with anti-Aβ1902 (D54D2) and anti-EEA1 1904 (610457) antibodies in hippocampal CA1region of 5×FAD/PV-Cre in EYFP, 40-Hz and random simulation conditions(scale bar=50 μm). FIG. 19B is a series of bar graphs depicting therelative immunoreactivity of Aβ normalized to EYFP in accordance withsome embodiments. In particular, FIG. 19B illustrates the relativeimmunoreactivity of Aβ normalized to EYFP (n=4 mice per group, 1908indicates p<0.05 and 1920 indicates p<0.01 by one-way ANOVA).

FIG. 20A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Aβ antibodies in hippocampal CA1 regionof 5×FAD/PV-Cre in accordance with some embodiments. In particular, FIG.20A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Aβ 2002 (12F4) antibodies in hippocampalCA1 region of 5×FAD/PV-Cre in EYFP, 40-Hz, and Random stimulationconditions (scale bar=50 μm). FIG. 20B is a bar graph depicting therelative immunoreactivity of Aβ normalized to EYFP in accordance withsome embodiments. In particular, FIG. 20B illustrates the relativeimmunoreactivity of Aβ normalized to EYFP (n=4 mice per group, 2004indicates p<0.05 and 2006 indicates p<0.001 by one-way ANOVA). Theintensity of Aβ-labeling was reduced by 39.5% following 40-Hzstimulation of FS-PV-interneurons in the three-month-old 5×FAD/PV-Crebi-transgenic mice and was significantly increased by 187.0% followingrandom stimulation, when compared to the EYFP group (see, e.g., FIGS.19A, 19B, 20A, and 20B, p<0.05 and p<0.01 by one-way ANOVA, n=4 mice pergroup).

Brain amyloid concentration may depend on Aβ production and clearancerates. In some embodiments, the Aβ peptides are produced by sequentialproteolytic cleavage of APP by β- and γ-secretases. When BACE1 cleavesAPP holoprotein, the CTFs and NTFs of APP may be produced. In someembodiments, to elucidate how 40-Hz stimulation reduced Aβ levels, gammaaffected APP cleavage was examined by measuring levels of the cleavageintermediates of APP, CTFs and NTFs, following FS-PV-interneuronstimulation. Following 40-Hz stimulation, a significant reduction wasfound of CTFs by 18.6% following 40-Hz stimulation compared to the EYFPgroup and by 19.7% compared to the random group (p<0.05 and p<0.01 byone-way ANOVA, n=6 mice per group).

FIG. 21A is a representative western blot, in accordance with someembodiments, depicting levels of APP (CT695), APP NTF (A8967), APP CTFs(CT695), and β-Actin (A5316) (loading control) in CA1 in in EYFP, Radom,and 40-Hz stimulation conditions, one mouse per lane, with twobiological replicates of each condition. FIG. 21B is a bar graphdepicting relative immunoreactivity of APP CTFs in accordance with someembodiments. In particular, FIG. 21B illustrates relative (normalized toactin) immunoreactivity of APP CTFs in 40-Hz versus EYFP and Randomconditions (n=6 mice per group, one asterisk 2102 indicates p<0.05, andtwo asterisks 2104 indicate p<0.01 by one-way ANOVA). FIG. 21C is aseries of western blots depicting levels of full-length APP 2106(CT695), APP CTFs 2108(CT695) and β-Actin 2112 (A5316, loading control)in CA1 in accordance with some embodiments. In particular, FIG. 21Cillustrates levels of full-length APP 2106 (CT695), APP CTFs 2108(CT695)and β-Actin 2112 (A5316, loading control) in CA1 in EYFP, Random, and40-Hz stimulation conditions, one mouse per lane, with two biologicalreplicates of each condition.

FIG. 22A is a bar graph depicting relative (normalized to actin)immunoreactivity of APP NTFs in 40-Hz versus EYFP and Random conditions(n=6 mice per group, notation “n.s” 2204 indicates not significant and2202 indicates p<0.05, by one-way ANOVA). FIG. 22B is a bar graphdepicting relative (normalized to actin) immunoreactivity of full-lengthAPP in EYFP, random, and 40-Hz conditions (n=6 mice per group by one-wayANOVA).

In some embodiments, following 40-Hz stimulation significant reductionof APP NTF levels were found by 28.5% compared to the EYFP group and by28.2% compared to the random group (see, e.g., FIGS. 21A, 22A, and 21C,p<0.05 by one-way ANOVA, n=6 mice per group). Moreover, the levels offull-length APP appeared to be similar among the various groups, showingthat the decrease in Aβ was not due to a change in precursor levels(see, e.g., FIGS. 21A, 22B, 21C, n=6 mice per group in APP experiments).In some embodiments, because of the relatively high abundance of APPcompared to its cleavage products in this mouse model, changes infull-length APP may be difficult to detect.

In some embodiments, processing of APP takes place within the vesiculartrafficking pathway, and prior work has shown APP is transported intorecycling endosomes following activity stimulation. Moreover, enlargedearly endosomes have been observed in brain tissue from AD patients andin human neurons derived from AD patients. In some embodiments, to testwhether gamma stimulation affected endosomal abundance in theexperimental animals, early endosomes have been characterized in CA1following 40 Hz and random stimulation using two markers, EEA1 (earlyendosomal antigen 1) and Rab5 (Ras-related protein encoded by the RAB5Agene). FIG. 23 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Rab5 (ADI-KAp-GP006-E) antibody inthree-month-old 5×FAD/PV-Cre mice in EYFP, 40-Hz, and random stimulationconditions (scaled bar=50 μm).

FIG. 24A is a bar graph representing the relative immunoreactivity ofEEA1 normalized to EYFP in accordance with some embodiments (n=4 miceper group, one asterisk 2402 indicates p<0.05 and two asterisks 2402indicate p<0.01 by one-way ANOVA). FIG. 24B is a bar graph depictingrelative Rab5 intensity levels of CA1 from 5×FAD/PV-Cre under EYFP,40-Hz, and random stimulation conditions in accordance with someembodiments (n=3 mice per group, three asterisks 2408 indicate p<0.001by one-way ANOVA). In some embodiments, EEA1 staining produced apunctate cytoplasmic and juxtamembrane pattern in the neuronal cellbodies, typical for early endosomes (see, e.g., FIG. 19A). In someembodiments, Rab5 labeling has been mostly restricted to the cell bodiesand plasma membrane, represented by small, thin puncta concentratedwithin endosomal and membrane compartments (see, e.g., FIG. 23).Altogether, early endosomal labeling of CA1 neurons demonstrated asignificant decrease in both EEA1 (39.7%) and Rab5 (40.1%) stainingintensity following 40-Hz stimulation compared to EYFP controls (see,e.g., FIGS. 19A, 23, 24A, p<0.05 and p<0.001 by one-way ANOVA, n 2sections from 3 mice per group). By contrast, random stimulation ofFS-PV-interneurons increased EEA1 staining intensity by 122% compared toEYFP controls (see, e.g., FIGS. 19A and 24A, p<0.01 by one-way ANOVA,n=2 sections from 3 mice per group). In some embodiments, thetreatment-dependent changes in EEA1 staining intensity paralleled thoseof Aβ in CA1 (see, e.g., FIGS. 19A-B, 20A-B, 23, and 24A-B, p<0.05 byone-way ANOVA, n=2 sections from 3 mice per group). These resultssuggest that in addition to observed changes in CTFs, 40-Hz stimulationalters EEA1 and Rab5, indicating differences in general endosomalprocessing.

FIG. 25A is a bar graph depicting levels of the AO peptide isoformAβ1-40 following different types of stimulation of the CA1 region of thehippocampus of a subject in accordance with some embodiments. In theexperiment, one hour of optogenetic stimulation of FS-PV+ at about 40 Hz502 decreased Aβ1-40 levels in hippocampal CA1. Excitatory pyramidalstimulation at 8 Hz 506 and excitatory pyramidal stimulation at 40 Hz508 did not significantly affect Aβ₁₋₄₀ levels. Random 40-Hz stimulation504, and particularly random excitatory pyramidal stimulation 510,significantly increased Aβ₁₋₄₀ levels (n=4-9 animals per group).

FIG. 25B is a bar graph depicting a decrease in the Aβ peptide isoformAβ₁₋₄₂ following stimulation of a specific cell type in the CA1 regionof the hippocampus of a subject with gamma oscillations in accordancewith some embodiments. In the experiment, one hour of optogeneticstimulation of FS-PV+ at about 40 Hz 516 decreased Aβ₁₋₄₂ levels inhippocampal CA1 (n=2-4 animals per group). Stimulation at 8 Hz 520,excitatory pyramidal stimulation at 40 Hz 522, and excitatory pyramidalstimulation at 8 Hz 524 increased Aβ₁₋₄₂ levels. Random 40-Hzstimulation 518, and particularly random excitatory pyramidalstimulation 526, significantly increased Aβ₁₋₄₂ levels).

FIG. 25C is a series of images illustrating an increase in the level offull-length APP 528, 534 (normalized to actin 532) and a decrease in thelevel of CTFs (e.g., β-CTF) 530, 536 (normalized to actin 532) followingstimulation of a specific cell type in the CA1 region of the hippocampusof a subject with gamma oscillations in accordance with someembodiments. Compared to the random 40-Hz control condition, FS-PV+stimulation at 40-Hz decreased APP β-CTF levels and increasedfull-length APP levels (n=4-6 animals per group). Because β-CTF is anAPP derivative produced during amyloidogenic cleavage of APP by BACE1,higher β-CTF levels represent increased Aβ production.

FIGS. 26A-26B are immunofluorescence images illustrating endosome levels(based on EEA1 levels) following different types of stimulation of theCA1 region of the hippocampus of a subject in accordance with someembodiments. In particular, a comparison of FIG. 26B to FIG. 26A showsthat induction of gamma oscillations through FS-PV+40-Hz stimulationreduces EEA1 levels (a marker for endosome levels) compared to randomFS-PV+ stimulation 900 as measured by immunofluorescence (n=3 mice pergroup, p=0.007). Decreased endosome levels in the cells indicatedecreased interaction between APP and β-secretase, which results indecreased APP cleavage and Aβ production. Thus, the study showed that,because increased endosome levels indicates increased APP processing andtherefore Aβ production, gamma oscillations reduce Aβ production in anAD mouse model.

FIG. 27 is a bar graph depicting mean intensity values (normalized toFAD) for the immunofluorescence images in FIGS. 26A-26B followingdifferent types of stimulation of the CA1 region of the hippocampus of asubject in accordance with some embodiments.

Gamma Stimulation Induced Morphological Transformation of Microglia.

In some embodiments, to further explore the cellular and moleculareffects of 40-Hz stimulation in an unbiased manner, genome-wide RNA-seqof hippocampal CA1 tissue following one hour of 40-Hz FS-PV-interneuronstimulation, or no stimulation (EYFP) of the 5×FAD/PV-Cre bi-transgenicmice was performed. In RNA-seq experiments, an average of 26,518,345sequencing reads was obtained from three stimulated and threenon-stimulated mice. Data QC analysis revealed an average value of 183for exon/intron ratio, an average value of 272 for exon/intergenicratio, and an average value of 3.6% for the percentage of ribosomal RNAreads. The analysis identified 523 differentially expressed genes(DEGs), with 130 of them up-regulated and 393 down-regulated in responseto 40-Hz stimulation.

FIG. 28 is a heat map presenting differentially expressed genesdetermined by whole transcriptome RNA-seq of mouse hippocampal CA1region with and without 40-Hz stimulation. Normalized z-score valueswere calculated for each differentially expressed gene (row). Colorsrepresent relatively low and high levels of gene expression. TABLE 2(below) presents 130 genes up-regulated by 40-Hz FS-PV-interneuronstimulation (p<0.05 using Cufflinks 2.2 software (available from theTrapnell Lab at the University of Washington, Seattle, Wash., forassembling transcripts, estimating their abundances, and testing fordifferential expression and regulation in RNA-seq samples)).

TABLE 2 Genes Up-Regulated by 40-Hz FS-PV-Interneuron Stimulation2010002N04Rik 2010300C02Rik 2410018L13Rik Adra2c Agfg2 Agxt2I1 Arc Atf3B2m BC018242 Beta-s Bst2 C1ga C1gb C1gc C1ql2 C1qtnf4 C3ar1 C4b Car7Card10 Cd68 Cebpb Cebpd Cirbp Cnn2 Cotl1 Crip2 Cst3 Ctxn1 Cyp2d22 DcakdEgr4 Erf F730043M19Rik Fam107a Fam163b Fmo2 Fn1 Gbp3 Gldc Gm129 Gm2115Gng7 Gpnmb Gpr25 Gpr37l1 Grm2 Gstm1 Gstm6 H1fx H2-D1 H2-k1 Hipk4 Hmox1I830012O16Rik Icam1 Icam5 Ifit1 Ifit3 Igfbp4 Igfbpl1 Irf7 Irf9 ItpkaJunb Kcnc4 Kcnh3 Kcnj4 Klf16 Lag3 Lcat Lefty1 Lgals3bp Lingo3 Lrg1 Ltbp4Lyz2 Metrn Mmp12 Mpped1 Mt1 Mt2 Mtap1s Npy Nr1d1 Nr4a1 Oasl2 Palm Parp14Pcsk1n Pdzd2 Pgls Phyhd1 Pitpnm2 Plekhg5 Pnpla7 Pou3f1 Ppp1r1a Prr7Prrt1 Rab40b Rara Rasl11b Rbm3 Rpph1 Rprml Sbk1 Scara3 Sh3bgrl3 Slc12a9Slc25a34 Slc29a4 Spp1 Spsb1 Ssbp4 Sstr4 Tfcp2l1 Thbs4 Thrsp Tmem198Tpst2 Trim30a Ttr Unc5a Ugcr11 Usp18 Vwf Wfs1 Xdh

TABLE 3 (below) presents 393 genes down-regulated by 40-HzFS-PV-interneuron stimulation (p<0.05 by Cufflinks 2.2 software(available from the Trapnell Lab at the University of Washington,Seattle, Wash.)).

TABLE 3 Genes Down-Regulated by 40-Hz FS-PV-Interneuron Stimulation1700003M02Rik 1700007K13Rik 1700009P17Rik 1700026D08Rik 1700027A23Rik1700028P14Rik 1700040L02Rik 1700094D03Rik 1810041L15Rik 2310039L15Rik2410004P03Rik 3110047P20Rik 3632451O06Rik 4930451C15Rik 4932411L154932425I24Rik 5730508B09Rik 6330406I15Rik A2m A330021E22RikA630089N07Rik AF529169 AU021034 AW551984 Adamts15 Adamts9 Adbyap1 Adra1bAebp1 Agt Aif1l Ak4 Ak7 Akap12 Amigo2 Amotl1 Ankrd29 Ankrd34c Ano1 Agp4Arhgap24 Asb2 Aspa Baiap3 Bbox1 Bmp7 Btbd11 C530008M17Rik Cacna2d2 Calb2Calr3 Camk2d Car10 Cast Cbln1 Cbln2 Cbln4 Ccdc108 Ccdc135 Ccdc136Ccdc141 Ccdc153 Codc19 Ccdc3 Ccdc40 Ccdc81 Cd109 Cd24a Cdh26 Cdhr3 Cdr1Cdr2 Chat Chgb Chrdl1 Chrna3 Chrna4 Chrnb3 Chrnb4 Cit Cited2 Clec18aClic6 Cntn6 Cntnap4 Cobl Coch Col12a1 Col8a2 Cpne4 Cpne9 Dach1 Dcn DcdDnahc5 Dnahc6 Dpp10 Dpy19l1 Dvnlrb2 Ebf1 Edil3 Efcab1 Efna5 Eif5a2Elavl2 Elavl4 Elfn1 Emb Enkur Eno4 Enox2 Epha8 Epn3 Ermn Etv1 Exph5Fabp7 Fam149a Fam196b Fam198b Fam19a4 Fbln7 Fgf1 Fgf10 Fhdc1 Foxj1 Foxp2Frem3 Fstl5 Fzd1 Fzd10 Galnt13 Gap43 Gatm Gdpd5 Gfra1 Gm6300 Gm7609Gm973 Gng8 Gpr115 Gpr123 Gpr139 Gpr151 Gpr153 Gpr26 Gpr4 Gprasp2 Gpx3Grb10 Gria4 Grid2ip Grin3a Grk4 Grm4 Gucy1a3 Hcn4 Hdc Hhip Hivep1 Hs6st2Hsp90aa1 Hsp90b1 Hspa4l Htr2c Htr5b Htr7 Hydin Inadl Igca Igub Irx1 Irx2Irx3 Itga3 Kcnc2 Kcng4 Kcnip1 Kcni12 Keni16 Kcnma1 Kcnn3 Kcng1ot1Kctd12b Kctd8 Kif9 Kit Kitl Klhl1 Lars2 Lbh Lbp Ldhd Lect1 Lef1 Lhfpl1Lhfpl3 Lhx9 Lrguk Lrrc23 Lrrc48 Lrrc55 Malat1 Mcf2 Megf11 Mgat4c Mlf1Mme Mob3b Mreg Mrvi1 Msi2 Mtfr1 Mum1I1 Musk Myb Mycbpap Myoc Ndn Necab1Necab2 Necab3 Nexn Nfam1 Ngb Nhlh2 Nppa Npr1 Nr4a2 Nrip3 Nrp2 Nrsn2Ntng1 Nudt4 Olfm3 Optn Otx2 Pamr1 Pbx3 Pcp4 Pcsk1 Pdp1 Peg10 Pgap1 Pgbd1Phactr2 Pirt Pkib Plagl1 Plcb4 Plch1 Plch2 Plcxd2 Pld5 Plekhg1 Plxnc1Popdc3 Pou4f1 Ppp1r32 Ppp1r36 Prkcd Prkch Prkcg Prkg2 Prokr2 Prr5l Prrg4Ptgds Ptpn14 Pvrl2 Pyrl3 Rab37 Ramp3 Ranbp3I Rap1gap Rasgef1b Rassf9Rbms3 Resp18 Ret Rgs16 Rgs3 Rgs4 Rgs6 Rims3 Rit2 Rnf152 Robo1 RorbRos6ka6 Rsph1 Rsph4a Rspo2 Scn1a Scube1 Scube3 Sema3d Sema6a Serpinf1Sgpp2 Sh3bgrl2 Shox2 Shroom3 Slc12a2 Slc17a6 Slc38a1 Slc39a4 Slc5a3Slc5a7 Slc6a9 Slc7a11 Slc9a4 Slco2a1 Slit2 Slitrk6 Sncg Sntn Socs2 Sox5Spag16 Spata18 Spock1 Spock3 Srgap1 St8sia2 Strbp Sv2b Synpo2 Syt15 Syt4Syt6 Syt9 Tac1 Tac2 Tacr1 Tcf7l2 Tekt1 Tex15 Tex9 Tgfb2 Th Timp2 Tm4sf1Tmem130 Tmem132c Tmem163 Tmem176a Tmem212 Tmem56 Tnc Tnnt1 Trhde Trim36Trim66 Trpc3 Trps1 Tsku Ttc18 Ttc21a Ttc39a Tyrp1 Ubxn10 Ugt8a Unc13cVangl1 Vat1 Vat1l Vav2 Vav3 Vwa5b1 Wbscr27 Wdr16 Wdr52 Wdr6 Wdr78 Wdr96Wfikkn2 Wif1 Wls Wnt3 Ysk4 Zcchc12 Zdbf2 Zdhhc22 Zfhx3 Zfp474 Zfp618Zfp941 Zic1 Zic2 Zic3 Zic4 Zic5

In some embodiments, up-regulated genes had generally higher expressionvalues than down-regulated genes. FIG. 29 is a box plot showing FPKMvalues of up- and down-regulated genes in EYFP and 40-Hz conditionsaccording to some embodiments. The box shows median (black lines in box)and quartiles (top and bottom of box), whiskers represent minimum andmaximum values, and circles represent outliers. Up-regulated genes mayhave been highly enriched in microglia. Specifically, about 35% of allup-regulated genes had their highest expression in microglia (with about19% in neurons, about 17% in endothelial cells, about 14% in astrocytes,about 9% in myelinating oligodendrocytes, about 5% in oligodendrocyteprecursor cells, and about 1% in newly formed oligodendrocytes).

FIG. 30 is a pie chart illustrating cell-type specific expressionpatterns of identified up-regulated genes following 40-Hz stimulation inaccordance with some embodiments. Gene FPKM values were calculated fromthe publicly available RNA-seq data from different brain cell types,including astrocytes, endothelial cells, microglia, myelinatingoligodendrocytes (MO), neurons, newly formed oligodendrocytes (NFo), andoligodendrocyte precursor cells (OPC). Thus, RNA-seq analysis stronglysuggests that one hour of 40-Hz stimulation of FS-PV-interneurons causedan alteration of the cellular state of microglia, which is significantgiven the accumulating evidence that these cells play a role in ADpathology.

In some embodiments, to further explore the potential effects of 40-Hzstimulation on microglia, a series of publicly available RNA-seqdatasets from microglia, peripheral macrophages, and neurons underdifferent chemical and genetic perturbations were compared to the genelists from characterization described in some embodiments herein usingGene Set Enrichment Analysis. TABLE 4 (below) illustrates GSEA-basedstatistical significance of correlation between genes up- ordown-regulated by 40-Hz stimulation and publicly available neuron,microglia and macrophage specific RNA-seq data under different chemicaland genetic perturbations.

TABLE 4 Nominal FDR Name of Perturbed Transcriptome NES p-value q-valueMCSF treated microglia 1.76 0.000 0.000 NMDA treated neurons 1.62 0.0000.000 IL34 treated microglia 1.59 0.000 0.000 GMCSF treated microglia1.49 0.005 0.004 Bicuculline treated neurons 1.49 0.016 0.013 ALS SOD1mutant microglia −1.26 0.050 0.028 LPS&IFNg treated macrophage (M1) 1.180.122 0.081 MeCP2 null microglia 1.16 0.164 0.127 IL4 treated macrophage(M2) −1.19 0.101 0.147 Huntington HTT mutant microglia 1.03 0.371 0.361Germ-free microglia 0.94 0.604 0.667 Tetrodotoxin treated neurons −0.760.941 0.970

Interestingly, the transcriptomic changes following 40-Hz stimulationwere more similar to those due to increased neural activity (by NMDA andbicuculline) and less similar to those due to silencing activity (bytetrodotoxin). These findings further support the observation that 40-Hzstimulation of FS-PV-interneurons does not decrease neuronal activity.Moreover, immediate early genes Nr4a1, Arc, and Npas4 that are known tobe up-regulated by neuronal activity, were elevated following one hourof 40-Hz stimulation shown by both RNA-seq and RT-qPCR. FIG. 31 is a bargraph illustrating RT-qPCR verification of specific gene targets in theRNA-seq data set in accordance with some embodiments. The bar graphshows relative RNA levels (fold change) from EYFP 3102, and 40-Hzstimulation 3104 conditions (one asterisk indicates p<0.05, twoasterisks indicate p<0.01, and three asterisks indicate p<0.001 byStudent's t-test, n=3 mice per group). Top down-regulated genes wereGrin4 and Camk2d (see, e.g., FIG. 31, p<0.05, n=3 mice per group).

Additionally, the transcriptomic results suggest a more phagocytic stateof microglia. In some embodiments, the up-regulated genes positivelycorrelated with genomic changes induced by macrophage colony-stimulatingfactor (MCSF) and granulocyte macrophage colony-stimulating factor(GMCSF), both known to promote microglial Aβ uptake. FIGS. 32A and 32Bare plots illustrating power spectral densities of local fieldpotentials recoded above the brain during 40 Hz light flicker inaccordance with some embodiments. FIGS. 32A and 32B show no increase inpower at 40 Hz, therefore the effect is not due to photoelectric effectson recording equipment or electrical noise (n=4, 2, 1, 1, 17, 42, 36,55, 53 40-Hz flicker periods from 4 recording sessions in three 5×FADanimals undergoing visual cortex recordings and from 5 recordingsessions in two 5×FAD and three WT mice undergoing hippocampalrecordings). Mean (solid line) and standard deviation (shaded area)across recordings are shown on the left (FIG. 32A) and per animal on theright (FIG. 32B). Recordings with less than 3 flicker periods 3202resulted in noisier power spectral densities than recordings with moredata 3204 but none showed evidence of peaks at 40 Hz. In someembodiments, RT-qPCR was carried out to validate the up-regulated genesinvolved in known microglia functions. It was confirmed that the genesassociated with microglial engulfment including Cd68, B2m, Bst2, Icam1,and Lyz2, were up-regulated in hippocampal CA1 region following 40-Hzstimulation.

FIG. 33 is a bar graph depicting RT-qPCR verification of specific genetargets in the RNA-seq data set in accordance with some embodiments.FIG. 33 shows relative RNA levels (fold change) in EYFP 3302 and 40-Hzstimulation 3304 conditions (one asterisk indicates p<0.05 and twoasterisks indicate p<0.01 by Student's t-test, n=6 mice per group).Other notable up-regulated genes included microglia-enrichedtranscriptional regulator Irf7, cell adhesion and migration regulatorSpp1, as well as microglia proliferation markers Csf1r and Csf2ra (see,e.g., FIG. 33, p<0.05 and p<0.01 by Student's t-test, n=6 mice pergroup). RT-qPCR also showed that the expression levels ofpro-inflammatory genes Il6, Il1b (11143), Itgam (CD11-b) and ananti-inflammatory gene Igf1 were not changed (see, e.g., FIG. 33, p>0.05by Student's t-test, n=6 mice per group). Thus the transcriptomicresults described herein suggest that 40 Hz neuronal stimulation inducedmicroglia into a state that promotes uptake.

Given the observations that 40-Hz stimulation up-regulated bothphagocytosis-related and migration/cell adhesion-related genes, themorphological features of microglia activation was examined. In someembodiments, an antibody that recognizes the microglial marker Iba1 tolabel microglia in hippocampal CA1 sections from the 5×FAD/PV-Cre miceafter one hour of 40 Hz, random or no stimulation (EYFP mice) was used.FIG. 34 is a series of immunofluorescence images illustratingimmunohistochemistry with anti-Iba1 3402 (019-19741) and anti-Aβ 3404(12F4) antibodies in hippocampal CA1 region of 5×FAD/PV-Cre mice inEYFP, 40-Hz, and Random stimulation conditions. Images were taken with40× objective scale bar=50 μm). Arrows indicate +Iba1/+Aβ signal in cellbody.

FIG. 35A is a bar graph depicting the number of microglia in EYFP and40-Hz conditions in accordance with some embodiments (n=2 sections from4 mice per group). FIG. 35B is a bar graph depicting the diameter ofmicroglial cell bodies normalized to EYFP in EYFP, 40-Hz, and Randomstimulation conditions in accordance with some embodiments (n=2 sectionsfrom 4 mice per group). FIG. 35C is a bar graph depicting the averagelength of microglia primary processes or projections normalized to EYFPin EYFP, 40-Hz, and Random stimulation conditions EYFP, 40 Hz andRandom. FIG. 35D is a bar graph depicting the percent of Iba1-positive(microglia) cell bodies that are also Aβ-positive in EYFP and 40-Hzstimulation conditions in accordance with some embodiments (n=2 sectionsfrom 4 mice group). Notation “n.s.” 3502 indicates not significant, twoasterisks 3504 indicate p<0.01, three asterisks 3506 indicate p<0.001,and four asterisks 3508 indicate p<0.0001 by one-way ANOVA.

First, the number of Iba1+ microglia in 6 animals per condition werecounted and almost twice as many microglial cells in the 40 Hz groupwere observed (15 microglial cells per 212.55 μm×212.55 μm region ofinterest (ROI)) compared to the unstimulated EYFP condition (mean of 8microglial cells per ROI) (see, e.g., FIGS. 34 and 35A, p<0.01 byone-way ANOVA, n=2 sections from 4 mice per group) and compared to therandom condition (mean of 10 microglial cells per ROI) (see, e.g., FIGS.34 and 35A, p<0.05 by one-way ANOVA, n=2 sections from 4 mice pergroup). Previous studies may have shown that two primary characteristicsof phagocytic microglia are increased cell body size and decreasedprocess length, therefore how these characteristics were affected by40-Hz stimulation were examined. In some embodiments, the diameter ofeach clearly labeled Iba1+ cell body in the field of view was measured.It was found that microglial cell body diameter increased by 135.3%following 40-Hz stimulation compared to no stimulation and by 138.7%compared to the random condition (see, e.g., FIGS. 34 and 35B, p<0.0001by one-way ANOVA, n=2 sections from 4 mice per group). The length ofprimary processes of microglia in each condition was measured and a54.0% reduction in primary microglia process length in the 40-Hzstimulation condition compared to EYFP controls and a 38.5% reductioncompared to random stimulation was observed (see, e.g., FIGS. 34 and35C, p<0.0001 by one-way ANOVA, n=2 sections from 4 mice per group).These findings were not affected by Iba1 levels as differences in Iba1expression between conditions were not observed in gene expressionanalysis described herein (see, e.g., TABLES 2 and 3). Thus, theincrease in cell body size and decrease in process length observed after40-Hz stimulation are morphological changes consistent with a shifttowards a phagocytic state for these microglia. Upon co-immunostainingwith an Aβ antibody (12F4, which does not cross-react with APP),potential co-localization of Aβ within microglia was evaluated as ameans to evaluate microglia Aβ uptake. The ratio of the number ofmicroglia with Aβ/Iba1 co-localization in the cell body (ImageJ, Fujico-localization plug-in) to the total number of microglia increased by54.9% following 40-Hz stimulation compared to EYFP controls, and by50.3% compared to random conditions, in CA1 neuropil where the Iba1+cells are primarily located (see, e.g., FIGS. 34 and 35D, p<0.01 byone-way ANOVA, n=2 sections from 4 mice per group). Iba1/signal overlapin microglial processes was excluded to avoid including potentiallyrandom, non-engulfment co-localization.

In some embodiments, to provide better resolution of the presence of Aβsignal within microglia, 3D renderings of microglia from this tissue andvideos from these renderings were created. FIG. 36 is a series of 3Drendering formed by merging immunofluorescence images from FIG. 34rotated 0 degrees 3602, −25 degrees around the Y-axis 3604, and 30degrees around the X-axis 3606 in accordance with some embodiments.Images were taken with 40× objective (scale bar=50 μm). Altogether, geneexpression and morphological analysis suggest that 40-Hz stimulationaffects microglia activity by increasing recruitment of microglial cellsto the site of stimulation and enhancing their engulfing activity,leading to an increased association with Aβ. Importantly, in someembodiments, evidence of neuronal loss by measuring thickness of the CA1cellular layer using nuclear staining with Hoechst was not found. Themean CA1 volume was not significantly different between EYFP and 40-Hzstimulation groups.

FIG. 37A is a series of immunofluorescence images illustratingimmunohistochemistry with Hoechst in hippocampal CA1 region of5×FAD/PV-Cre in EYFP and 40-Hz stimulation conditions in accordance withsome embodiments. FIG. 37B is a bar graph depicting the estimated CA1thickness of 5×FAD/PV-Cre in EYFP and 40-Hz stimulation conditions inaccordance with some embodiments (n=4 mice per group, “n.s.” indicatesnot significant by Student's t-test).

Next, differential gene expression in 5×FAD mice infected with theAAV-DIO-ChR2-EYFP and stimulated with 40-Hz FS-PV+ stimulation (TREAT)or control stimulation (CTRL) was assessed by genome-wide RNA-seq ofhippocampal CA1 following one hour of stimulation according to someembodiments. FIG. 38A is a heat map displaying 523 differentiallyexpressed genes (DEGs) determined by genome-wide RNA-seq of hippocampalCA1 upon TREAT or CTRL in accordance with some embodiments. Each row inFIG. 38A represents a DEG, and the columns in FIG. 38A represent thetranscriptomic profiles of three individual control animals and threeindividual treated (40-Hz FS=PV+ stimulated) animals.

FIG. 38B is a chart illustrating overlap between DEGs up-regulated inthe TREAT condition in FIG. 38A in accordance with some embodiments. InFIG. 38B, the induction of gamma oscillations through FS-PV+40-Hzstimulation reduces Iba1 levels compared to random FS-PV+ stimulation asmeasured by immunofluorescence (n=3 mice per group, p=0.006). FIG. 38Bshows that the up-regulated genes in the TREAT condition overlapsignificantly and specifically with microglia genes up-regulated byanti-inflammatory microglia activation (i.e., MCSF genes). Genes wereupregulated in microglial cells to a greater extent than in astrocytes,endothelial cells, myelinating oligodendrocytes (MOs), neurons, newlyformed oligodendrocytes (NFOs), and oligodendrocyte precursor cells(OPCs). TABLE 5 (below) presents microglia/macrophage pathways forup-regulated genes.

TABLE 5 Nominal FDR Name of Perturbed Transcriptome NES p-value q-valueMCSF treated microglia 1.76 0.000 0.000 IL34 treated microglia 1.590.000 0.000 GMCSF treated microglia 1.49 0.005 0.004 LPS&IFNg treatedmacrophage (M1) 1.18 0.122 0.081 IL4 treated macrophage (M2) −1.2 0.1010.147

According to some embodiments, RT-qPCR was conducted to verify specificgene targets from the RNA-seq data set. FIG. 39 is a bar graph depictingRT-qPCR verification of specific gene targets in the RNA-seq data set ofFIG. 38A in accordance with some embodiments. In particular, FIG. 39shows the fold change (normalized to GAPDH) of specific gene targets incontrol and treated conditions, including the genes CSF1, CSF1R, 11-6,111-Beta, CD11-b, CYBA, Hmox1, H2-K1, Lgals3, and Icam1.

FIG. 40 is a plot illustrating the biological processes to which theup-regulated genes of FIG. 38A relate in accordance with someembodiments. Importantly, the up-regulated genes in FIG. 40 arespecifically associated with immune-related processes. Upregulated genesbelonged to immune-related biological processes includinglymphocyte-mediated, adaptive immune, and immunoglobulin-mediatedprocesses. FIG. 41 is a plot illustrating the biological processes towhich the down-regulated genes of FIG. 38A relate in accordance withsome embodiments. Down-regulated genes belonged to biological processesincluding cell motion, cell-cell signaling, synaptic transmission,locomotory behavior, and neuron projection, as shown in FIG. 41.

FIG. 42A is a series of immunofluorescence images illustrating levels ofIba1 following different types of stimulation of the CA1 region of thehippocampus of a subject in accordance with some embodiments. FIG. 42Bis a bar graph depicting mean intensity values for theimmunofluorescence images in FIG. 42A in accordance with someembodiments. FIG. 42A shows that the endosome levels are reduced byoptogenetic enhancement of gamma rhythm. Induction of gamma oscillationsthrough FS-PV+40-Hz stimulation reduced levels of EEA1 (a marker forendosomes) as measured by immunofluorescence (n=3 mice per group,p=0.08). The results showed that, because increased endosome levelsindicate increased APP processing and therefore Aβ production, gammaoscillations reduce Aβ production in the AD mouse model.

Taken together, the results of the study showed that restoration orinduction of gamma rhythms recovered molecular pathology in a mousemodel of AD. The cell-type specific and temporally precisereintroduction of gamma oscillations through optogenetics both reducedgeneration and enhanced clearance of isoforms Aβ₁₋₄₀ and Aβ₁₋₄₂,peptides which aggregate to initiate many degenerative cascades involvedin AD neuropathology. Furthermore, this treatment inducedanti-inflammatory microglia signaling pathways, counteracting immunemechanisms linked to neurodegeneration.

According to some embodiments, cell-type specific and temporallycontrolled gamma oscillations may be induced in the hippocampus, thevisual cortex, the barrel cortex, and/or the auditory cortex withoutoptogenetics.

Visual Stimulation at Gamma Frequency Non-Invasively Drove GammaOscillations in the Visual Cortex.

The profound reduction of Aβ levels by optogenetic stimulation at 40 Hzled to exploring other ways to induce 40-Hz oscillations in the brain toensure this effect was not somehow specific to optogenetic manipulationsor invasive procedures. In order to examine whether light flickeringcould be used as a non-invasive approach to induce 40-Hz oscillations inthe visual cortex, in some embodiments, animals were exposed to periodsof 40 Hz or random flickering, and continuous lights on interleaved withperiods of darkness.

FIG. 43A is a schematic diagram illustrating a mouse exposed to lightflicker stimulation in accordance with some embodiments. To determine ifthis light flickering altered Aβ, the animals were exposed to 40-Hzlight flickering for one hour, consistent with the duration ofoptogenetic stimulation that reduced Aβ as described herein. Lightflickering covered the animals' entire field of view. As controls formolecular and cellular assays, the three-month-old 5×FAD mice weremaintained in constant dark for three days or were treated for one hourwith either constant light or 20-Hz flickering lights, or 80-Hzflickering lights (see, e.g., FIG. 43A).

FIG. 43B includes a local field potential trace in the visual cortexbefore and during 40-Hz light flicker and a plot of power spectraldensity in accordance with some embodiments. Mean (solid line) andstandard deviation (shaded area) of power spectral density are indicatedduring 40-Hz light flicker 4302, random light flicker 4304, or dark 4306in visual cortex (n=4 5F×FAD mice from 5 recording sessions). FIGS.43C-43F are plots depicting power spectral densities of local fieldpotentials in the visual cortex during 40-Hz light flicker, random lightflicker, constant dark, and constant light, respectively, for eachrecording session for each mouse in accordance with some embodiments(n=5 recordings from four 5×FAD mice with 47, 51, 61, 49, 16 40-Hzflicker, 47, 50, 64, 50, 16 random flicker, 279, 302, 382, 294, 93 dark,and 47, 50, 64, 49, 15 light periods). In visual cortex, it was foundthat light flickering at 40 Hz increased power in the LFPs at 40 Hz(see, e.g., FIGS. 43B and 43C), while random interval light flickeringand dark did not (see, e.g., FIGS. 43B, 43D, and 43E).

FIG. 44A is a series of histograms depicting fraction of spikes invisual cortex as a function of time for four cycles of 40-Hz lightflicker and an equivalent period of time for random light flicker inaccordance with some embodiments. FIG. 44A illustrates a histogram offraction of spikes in visual cortex as a function of time for 4 cyclesof 40-Hz light flicker 4402 or equivalent period of time of random lightflicker 4404 (n=four 5×FAD mice from five recording sessions, barindicates mean and error bars indicate SEM across animals). Bar aboveindicates when light was on 4406 or off 4408. In some embodiments,spiking increased and decreased as the light flickered on and offresulting in spiking phase locked to the 40-Hz frequency during 40-Hzstimulation (histogram 4402 in FIG. 44A) but no clear frequency emergedduring random stimulation (histogram 4404 in FIG. 44A).

FIG. 44B is a series of electrical traces of local field potentialsrecorded above the brain during light flicker in accordance with someembodiments. In some embodiments, no increase in 40 Hz power during40-Hz flicker was found when recorded from saline just above the brain,showing that this effect was not due to photoelectric effects orelectrical noise (see, e.g., FIGS. 32 and 44B). As with optogeneticstimulation, the random flicker provided a control for overall changesin activity due to light flicker.

FIG. 45A is a histogram illustrating the difference in firing ratesbetween 40-Hz light flicker and random light flicker in accordance withsome embodiments (n=226 stimulation periods from five recording sessionsin four 5×FAD mice). FIG. 45B is a plot illustrating multi-unit firingrates in visual cortex during 40-Hz light flicker, random light flicker,dark, and light periods in accordance with some embodiments FIG. 45Billustrates multiunit firing rates in visual cortex. Box and whiskerplots show median (white lines in box) and quartiles (top and bottom ofbox). In all animals firing rates between 40-Hz flicker and randomflicker conditions were not significantly different showing that therandom stimulation condition serves as a control for spiking activity(ranksum tests for each of 5 recording session from four 5×FAD mice,p>0.06, median and quartiles shown in figure, n=47, 51, 64, 49, 16 40-Hzflicker periods and 47, 50, 64, 50, 16 random flicker periods perrecording). There were no significant differences in firing ratesbetween 40-Hz flicker and light conditions indicating that 40-Hz lightflicker generally did not cause neuronal hyper-excitability (ranksumtests for each of 5 recording session from four 5×FAD mice, p>0.2 for 4recording sessions, p<0.01 for 1 recording session, which is notsignificant, when corrected for performing multiple comparisons, medianand quartiles shown in figure, n=47, 51, 64, 49, 16 40 Hz periods and47, 50, 64, 49, 16 light periods per recording). In one session, therewas more activity in the 40-Hz stimulation than in the dark condition.Differences in multi-unit firing rates between 40 Hz and random flickerperiods tended to be near zero (see, e.g., 45 A); and comparing theseperiods within animals no significant differences were found (see, e.g.,FIG. 45B, ranksum tests for each of 5 recording session from four 5×FADmice, p>0.06, median and quartiles shown in figure, n=47, 51, 64, 49, 16gamma flicker periods and 47, 50, 64, 50, 16 random flicker periods perrecording).

Visual Stimulation at Gamma Frequency Decreased AβLevels in the VisualCortex.

Given the efficacy of the optogenetic method, a translational,non-invasive amyloid reduction treatment was designed. FIG. 46A is aschematic diagram illustrating an experimental paradigm in accordancewith some embodiments. As shown in FIG. 46A, a first subset of AD modelmice were placed in a first chamber 4600 with a 40-Hz flashing light,and a second subset of AD model mice were placed in a second chamber4602 that was kept dark. The animals in the first chamber 4600 wereexposed to the 40-Hz flashing light for about one hour.

FIGS. 46B and 46C are plots further illustrating changes in baselinelevels of Aβ peptide isoforms Aβ₁₋₄₀ and Aβ₁₋₄₂, respectively, followingthe experimental paradigm in FIG. 46A in accordance with someembodiments. FIG. 46B shows that 40-Hz light exposure in the visualcortex V1 of 5×FAD mice significantly reduced Aβ₁₋₄₀ and Aβ₁₋₄₂ levels.Levels of Aβ₁₋₄₀ and Aβ₁₋₄₂ are presented as pg/mL (n=6 animals pergroup).

Given that 40-Hz light flicker drives 40-Hz oscillations in the primaryvisual cortex and that optogenetic induction of 40-Hz oscillationsreduced hippocampal Aβ levels, the aim was to determine whether 40-Hzlight flicker could reduce Aβ levels in the visual cortex. For theseexperiments, in some embodiments, pre-symptomatic three-month-old 5×FADmice were used. The mice were placed in a dark box and exposed to either40-Hz light flicker, constant light on (light), or constant light off(dark) for one hour.

FIGS. 47A and 47B are bar graphs depicting changes in baseline levels ofAβ₁₋₄₀ and Aβ₁₋₄₂, respectively, in 5×FAD visual cortex in dark, light,40-Hz flicker, 20-Hz flicker, 80-Hz flicker, 40-Hz flicker withpicrotoxin (PTX) and Random flicker conditions in accordance with someembodiments (n=12 mice per group for dark; n=6 mice per group for light,40-Hz flicker, 20-Hz flicker, 80-Hz flicker, and PTX; n=4 mice per groupfor Random flicker; “n.s.” indicates not significant, one asteriskindicates p<0.05, and two asterisks indicate p<0.01 by one-way ANOVA).FIGS. 47 and 47B show mean and SEM. Circles superimposed on bars in thebar graphs indicate individual data points in each group. Following onehour after light exposure, it was observed that Aβ₁₋₄₀ levels in visualcortex were reduced by 57.96% and Aβ₁₋₄₂ levels by 57.97% compared tothe dark condition (as measured by Aβ ELISA, see, e.g., FIGS. 47A and47B, p<0.05 by one-way ANOVA, n=6 mice per group). Compared to lightcontrols, amyloid levels were reduced by 62.47% (Aβ₁₋₄₀) and 68.55%(Aβ₁₋₄₂) following one hour of 40-Hz flicker (as measured by Aβ ELISA,see, e.g., FIG. 4′7, p<0.05 by one-way ANOVA, n=6 mice per group).Furthermore, the effect was specific to 40-Hz flicker as neither 20-Hz,80-Hz, nor random flicker significantly reduced Aβ levels compared todark and light controls (see, e.g., FIG. 47, “n.s.” indicates notsignificant, n=6 mice per group).

In some embodiments, to test regional specificity Aβ levels in thesomatosensory barrel cortex (BC) was examined and no significantdifferences were found. FIG. 48A is a bar graph depicting relativeAβ₁₋₄₀ and Aβ₁₋₄₂ levels of 5×FAD barrel cortex under dark and 40-Hzflicker conditions in accordance with some embodiments (n=3 mice pergroup; “n.s.” indicates not significant by Student's t-test). When 5×FADmice were pretreated with a low dose GABA-A antagonist (picrotoxin, 0.18mg/kg, which does not induce epileptic activity), the effects of 40-Hzflicker on Aβ levels were completely abrogated, indicating thatGABAergic signaling, most likely from the FS-PV-interneurons, isnecessary for this effect (see, e.g., FIG. 47, “n.s.” indicates notsignificant, n=6 mice per group).

To demonstrate the effect was not specific to the 5×FAD mouse, thisresult was replicated in a different AD model, the APP/PS1 mouse, a wellvalidated model with two familial AD mutations (APP Swedish and PSEN1deltaE9). FIG. 48B is a bar graph depicting changes in baseline levelsof Aβ₁₋₄₀ and Aβ₁₋₄₂ in APP/PS1 visual cortex under dark and 40-Hzflicker conditions in accordance with some embodiments (n=5 mice pergroup for dark and n=4 mice per group for 40-Hz flicker conditions;“n.s.” indicates not significant and one asterisk indicates p<0.05, byStudent's t-test).

FIG. 48C is a bar graph depicting changes in baseline levels of Aβ₁₋₄₀and Aβ₁₋₄₂ in WT visual cortex under dark and 40-Hz flicker conditionsin accordance with some embodiments (n=11 mice per group for dark andn=9 mice per group for 40-Hz flicker conditions; one asterisk indicatesp<0.05, by Student's t-test). In some embodiments, in the APP/PS1 micefollowing 40-Hz flicker treatment, significantly reduced Aβ₁₋₄₀, by20.80%, and a trend of reduced Aβ₁₋₄₂, by 37.68% was found, though thelatter was not significantly different from dark conditions (see, e.g.,FIG. 48B, Aβ₁₋₄₀p<0.05, Aβ₁₋₄₂p<0.09—not significant by Student'st-test, n=5 mice per group for dark, n=4 mice per group for 40-Hzflicker). In addition in aged WT mice, a 58.2% reduction in endogenousmouse Aβ₁₋₄₀ following one hour 40-Hz flicker was found (see, e.g., FIG.48C, p<0.05 by Student's t-test, n=11 dark mice and n=9 40-Hz flickermice). Aβ₁₋₄₂ was below detectable levels for both flicker and controlgroups in these animals. The reduction of endogenous mouse Aβ₁₋₄₀ in WTanimals reveals these results may not be restricted to Tg APP expressionor mutant APP; rather they may extend to Aβ produced from APP withexpression driven by its endogenous promoter. FIGS. 48A-48C show meanand SEM.

Next, in some embodiments, an investigation as to whether 40-Hz flickeralters microglia activity in the visual cortex in the same manner that40 Hz optogenetic FS-PV-interneuron stimulation altered hippocampal CA1microglia was conducted. FIG. 49 is a series of immunofluorescenceimages illustrating immunohistochemistry with anti-Iba1 (019-19741) andanti-Aβ 4904 (12F4) antibodies in 5×FAD visual cortex under dark and40-Hz flicker conditions in accordance with some embodiments. The imageswere taken with 40× objective (scale bar=50 μm). Right: 120× zoom;arrows indicate +Iba1/+Aβ signal in cell body.

FIG. 50A is a bar graph depicting the number of microglia in dark and40-Hz flicker conditions in accordance with some embodiments (n=2sections from 4 mice per group; “n.s.” indicates not significant byStudent's t-test). FIG. 50B is a bar graph depicting the diameter ofmicroglial cell bodies normalized to control in dark and 40-Hz flickerconditions in accordance with some embodiments (n=2 sections from 4 miceper group; two asterisks indicate p<0.01 by Student's t-test). FIG. 50Cis a bar graph depicting the average length of microglia primaryprocesses normalized to control in dark and 40-Hz flicker conditions inaccordance with some embodiments (n=2 sections from 4 mice per group;four asterisks indicate p<0.0001 by Student's t-test). FIG. 50D is a bargraph depicting the percent of Iba1-positive (microglia) cell bodiesthat are also Aβ-positive under dark and 40-Hz flicker conditions inaccordance with some embodiments (n=2 sections from 4 mice per group;two asterisks indicate p<0.01 by Student's t-test). FIGS. 50A-50D showmean and SEM.

In some embodiments, Iba1 was used to label microglia in visual cortexsections of 5×FAD mice after one hour of 40-Hz flicker or darkconditions (see, e.g., FIG. 49). While microglia number was notdifferent between dark and 40-Hz flicker conditions (see, e.g., FIGS. 49and 50A, “n.s.” indicates not significant, n=2 sections from 4 mice pergroup) the microglial cell body diameter increased by 65.8% following40-Hz flicker in the visual cortex compared to dark controls (see, e.g.,FIGS. 49 and 50B, p<0.01 by Student's t-test, n=2 sections from 4 miceper group). The lengths of microglia primary processes were reduced by37.7% in 40-Hz flicker conditions compared to dark controls (see, e.g.,FIGS. 49 and 50C, p<0.0001 by Student's t-test, n=2 sections from 4 miceper group). Because the microglia in the visual cortex had morphologyindicative of enhanced engulfment activity, in some embodiments, thenumber of Aβ-bearing microglia was examined. For this experiment, visualcortex sections were co-labeled with Iba1 and Aβ(12F4) antibodies.Aβ/Iba1 co-localization in the cell body was increased by 33.5% in 40-Hzflicker conditions, which indicated that 40-Hz flicker resulted in moreAβ-bearing microglia than dark control conditions (see, e.g., FIGS. 49and 50D, p<0.01 by Student's t-test, n=2 sections from 4 mice pergroup).

In some embodiments, to provide better resolution of the morphologicalchange in microglia, CLARITY was used to create 3D renderings ofmicroglia from 100 μm sections of visual cortex and videos were createdfrom these renderings. FIG. 51 is a series of 3D renderings (fromimmunofluorescence images) of Iba+ microglia under dark and 40-Hzflicker conditions from CLARITY-treated 100 μm tissue sections rotated0° 5102, 45° around the X-axis 5104, and 45° around the Y-axis 5106.Images were taken with 63× objective (scale bar=15 μm). Finally, todemonstrate that microglia indeed engulf Aβ in the 5×FAD mouse,microglia from 5×FAD and WT animals were purified usingfluorescence-activated cell sorting (FACS) and Aβ levels were analyzedvia ELISA.

FIG. 52A is a flow diagram illustrating a method of isolating microgliafrom a visual cortex using fluorescence-activated cell sorting (FACS) inaccordance with some embodiments. Visual cortex was dissected, and thensingle cells were suspended and labeled with CD11b and CD45 antibodies.Subsequently, cells were sorted via fluorescence-activated cell sorting(FACS) and lysed. Aβ₁₋₄₀ levels were analyzed by ELISA. FIG. 52B is abar graph depicting Aβ₁₋₄₀ levels in microglia isolated from the visualcortices of three-month-old 5×FAD and WT control animals using themethod of FIG. 52A in accordance with some embodiments (n=8 mice pergroup for 5×FAD and n=4 mice per group for WT mice; one asteriskindicates p<0.05 by Student's t-test). Circles superimposed on bars inbar graphs indicate individual data points in each group.

FIG. 53A is a series of immunofluorescence images illustratingimmunohistochemistry with SVP38 antibodies to detect synaptophysin inthree-month-old 5×FAD visual cortex under dark and 40-Hz flickerconditions in accordance with some embodiments. Images were taken with40× objective (scale bar=50 μm). Right: 100× of dark and 40-Hz flickerconditions. FIG. 53B is a bar graph depicting relative SVP38 intensitylevels of 5×FAD visual cortex after in dark and 40 Hz flicker conditionsin accordance with some embodiments (n=4 mice per group; “n.s.”indicates not significant, by Student's t-test).

It was found that the microglia-specific levels of Aβ are significantlyhigher in 5×FAD animals than WT controls, with levels at 27.2 pg/10⁴microglia in 5×FAD mice and 9.78 pg/10⁴ microglia in WT control mice(see, e.g., FIGS. 52A and 52B, p<0.05 by Student's t-test, n=8 for 5×FADand n=4 for WT mice). Aβ₁₋₄₂ was below detectable levels for bothflicker and control groups in these animals. Overall, the transformationof microglia in visual cortex induced by 40-Hz stimulation appearedsimilar to that which occurred in hippocampal CA1. Additionally,synaptophysin levels did not change between dark and 40-Hz flickerconditions, indicating that microglia activation did not significantlyincrease engulfment of synapses (see, e.g., FIGS. 53A and 53B, “n.s.”indicates not significant, n=2 sections from 4 mice per group). Takentogether, the data disclosed herein demonstrate that 40-Hz oscillationsinduced non-invasively via sensory stimulation may effectively reduce Aβabundance and promote microglia/Aβ interactions in an AD mouse model.Furthermore 40-Hz stimulation may reduce Aβ in two distinct braincircuits, suggesting a general mechanism by which gamma oscillationsreduce amyloid abundance and enhance microglia phagocytosis in variousbrain regions.

In a further experiment, Aβ₁₋₄₂ levels were assessed following one hourof exposure to the dark (no light), a 20-Hz flashing light, a 40-Hzflashing light, or an 80-Hz flashing light, wherein 20 Hz and 80 Hz areharmonics of 40 Hz. However, only the 40-Hz flashing light flickerreduced Aβ₁₋₄₂ levels significantly. FIG. 54A is a bar graphillustrating a decrease in the AO peptide isoform Aβ₁₋₄₂ followingstimulation of the visual cortex of a subject with gamma oscillations inaccordance with some embodiments.

Another study was conducted to assess the timing of the reduction ofAβ₁₋₄₂ levels. For one hour, mice were exposed to either no light or a40-Hz flashing light. The Aβ₁₋₄₂ levels were determined following onehour of treatment and again 24 hours after treatment completion. FIG.54B is a bar graph illustrating levels of the Aβ peptide isoform Aβ₁₋₄₂after stimulation of the visual cortex of a subject with gammaoscillations and again twenty-four hours after the stimulation inaccordance with some embodiments. Although Aβ levels remained reducedtwenty four hours after the treatment, the reduction was smaller thanimmediately after treatment.

Visual Stimulation at Gamma Frequency Did not Affect Aβ Levels in theHippocampus.

To determine if visual stimulation by light flicker could affect braincircuits implicated in AD, in some embodiments, the effects of lightflicker on hippocampus, one of the brain regions affected early in thecourse of AD in humans were examined. FIG. 55A includes an electricaltrace of a local field potential in the hippocampus before and during40-Hz light flicker 5502 and a plot of power spectral densities inaccordance with some embodiments. Mean (solid line) and standarddeviation (shaded area) of power spectral density during dark 5504,40-Hz light flicker 5506, and random light flicker 5508 in CA1 (n=two5×FAD and three WT mice).

FIG. 55B is a series of histograms of fractions of spikes in thehippocampus as a function of time for 4 cycles of 40-Hz light flicker5510 and the equivalent period of time for random light flicker 5512,respectively, in accordance with some embodiments (n=two 5×FAD and threeWT mice, bar indicates mean and error bars indicate SEM across animals).Bar above indicates when light was on (white) or off (black). For randomstimulation, spiking was aligned to the start of the light turning on,additional periods with light occurred at random intervals indicated bygrey. Using the same approach to examine the effects of light flicker inCA1 as disclosed herein in visual cortex, it was found that lightflickering at 40 Hz increased power in the LFPs recorded at 40 Hz (see,e.g., FIG. 55A and graph 5510 in FIG. 55B), while random interval lightflickering (random flicker) and dark did not (see, e.g., FIG. 50D, graph4310 in FIG. 43C). Spiking was also modulated by the 40-Hz flickerfrequency during 40 H stimulation, however, the modulation appearedsmaller than in visual cortex (see, e.g., FIG. 55B, hippocampus, FIG.44A, visual cortex).

FIG. 56A is a histogram illustrating the difference in firing ratesbetween 40-Hz light flicker and random light flicker in accordance withsome embodiments (bottom n=168 stimulation periods from 5 recordingsessions in two 5×FAD and three WT mice). FIG. 56B is a plotillustrating multi-unit firing rates in CA1 during 40-Hz light flicker5604, random light flicker 5605, dark 5602, or light 5608 periods inaccordance with some embodiments. Box and whisker plots show median(white lines in box) and quartiles (top and bottom of box). In allanimals firing rates between 40-Hz flicker and random flicker conditionswere not significantly different showing that the random stimulationcondition serves as a control for spiking activity (ranksum tests foreach of 5 recordings from two 5×FAD and three WT animals, p>0.2, medianand quartiles shown in figure, n=22, 54, 42, 71, 55 40-Hz flickerperiods and 12, 34, 32, 54, 36 random flicker periods per recording).There were no significant differences in firing rates between 40-Hzflicker and light conditions indicating that 40-Hz light flickergenerally did not cause neuronal hyper-excitability (ranksum tests foreach of 5 recordings from two 5×FAD and three WT animals, p>0.3, medianand quartiles shown in figure, n=22, 54, 42, 71, 55 40 Hz periods and12, 34, 33, 54, 35 light periods per recording).

As in visual cortex, differences in multi-unit firing rates between 40Hz and random flicker periods tended to be near zero (see, e.g., FIG.56A), and in comparing these periods within animals, no significantdifferences were found (see, e.g., FIG. 56B, ranksum tests for each of 5recording session from four 5×FAD mice, p>0.06, median and quartilesshown in figure, n=22, 54, 42, 71, 55 40-Hz flicker periods and 12, 34,32, 54, 36 random flicker periods per recording).

In some embodiments, the effect of visual light flicker on levels of Aβin hippocampus was examined, using the same approach used in visualcortex. FIG. 57A is a bar graph depicting relative Aβ₁₋₄₀ levels in5×FAD visual cortex, and FIG. 57B is a bar graph depicting relativeAβ₁₋₄₂ levels in 5×FAD visual cortex in accordance with some embodiments(n=4 mice per group; “n.s.” indicates not significant). In contrast towhat was observed in visual cortex, in CA1 a significant difference inAβ₁₋₄₀ and Aβ₁₋₄₂ levels one hour after 40-Hz flicker or randomstimulation was not found. Aβ levels following 40-Hz flicker or randomflicker were not significantly different from the dark condition: Aβ₁₋₄₀levels were 108.4% and 96.82% of the dark condition following 40 Hz andrandom flicker, respectively, and Aβ₁₋₄₂ levels were 118.8% and 92.15%of the dark condition following 40-Hz and random flicker, respectively(see, e.g., FIGS. 57A and 57B, “n.s.” indicates not significant, n=4mice per group). Thus, one hour of 40-Hz light flicker did notsignificantly reduce levels of Aβ in hippocampus.

Chronic Visual Stimulation at Gamma Frequency Decreased Plaque Load inthe Visual Cortex.

The affected amyloid abundance in pre-plaque 5×FAD mice when 40-Hzoscillations are driven either optogenetically or by visual stimulationvia light flicker have been examined and disclosed herein. Next, the aimwas to determine whether this treatment was effective in animals thatalready show plaque load. To this end, in some embodiments,six-month-old 5×FAD mice were used, as they develop extensive amyloidplaque pathology in many brain regions including visual cortex. A testwas conducted to see what happens to the advanced Aβ-related pathologyfollowing non-invasive gamma stimulation. To investigate the duration ofAβ reduction in response to one hour of 40-Hz flicker, in someembodiments, Aβ levels were measured in the visual cortex 4, 12, and 24hours after one hour of 40-Hz flicker or dark conditions.

FIGS. 58A and 58B are bar graphs depicting relative Aβ₁₋₄₀ and Aβ₁₋₄₂levels, respectively, of 5×FAD visual cortex 1, 4, 12, and 24 hoursfollowing one hour of dark or 40-Hz flicker treatment in accordance withsome embodiments (n=4 mice per group for 4 and 12 hour wait, n 6 for 1and 24 hour wait, n=12 for dark; “n.s.” indicates not significant, oneasterisk indicates p<0.05 and two asterisks indicate p<0.01, by one-wayANOVA). The results showed that after 4 hours, Aβ₁₋₄₀ levels werereduced by 63.4% and Aβ₁₋₄₂ levels were reduced by 63.2% compared todark controls (see, e.g., FIG. 58, p<0.01, n=4 mice per group). By 12hours, Aβ₁₋₄₀ levels were reduced by 50.9% while Aβ₁₋₄₂ levels were notsignificantly different from dark controls (see, e.g., FIG. 58, “n.s.”indicates not significant and p<0.01, n=4 mice per group). Finally, 24hours following one hour of 40-Hz flicker treatment, soluble Aβ₁₋₄₀ andAβ₁₋₄₂ levels were not significantly different in 40-Hz flicker comparedto dark control conditions (see, e.g., FIG. 58, “n.s.” indicates notsignificant, n=6 mice per group for 24 hours and n=4 mice per group fordark). These results indicate that the effects of 40-Hz flickertreatment are transient.

Therefore, to disrupt advanced plaque pathology, in some embodiments,mice were treated for one hour each day for seven days with 40-Hzflicker or, for control, with dark conditions. FIG. 59A is a schematicdiagram depicting six-month-old mice exposed to one hour of flicker perday for seven days in accordance with some embodiments. FIG. 59B is abar graph illustrating relative Aβ₁₋₄₂ levels in visual cortices ofsix-month-old 5×FAD mice after seven days of one hour/day under dark or40-Hz flicker conditions in accordance with some embodiments (n=13 miceper group, two asterisks indicate p<0.01 and three asterisks indicatep<0.001, Student's t-test). FIG. 59C is a bar graph illustratingrelative Aβ₁₋₄₀ levels in visual cortices of six-month-old 5×FAD miceafter seven days of one hour/day under dark or 40-Hz flicker conditionsin accordance with some embodiments (n=13 mice per group, one asteriskindicates p<0.01 and two asterisks indicate p<0.01, by Student'st-test). FIGS. 59B and 59C show mean and SEM. Circles superimposed onbars in the bar graphs indicate individual data points in each group.

At the conclusion of the seven-day period, the visual cortex wasanalyzed by ELISA and immunostaining. In some embodiments, the tissuewas lysed in phosphate-buffered saline (PBS) to extract the PBS solubleAβ fraction and it was found that seven days of one hour 40-Hz flickerreduced soluble Aβ₁₋₄₀ and Aβ₁₋₄₂ levels by 60.5% and 51.7%respectively, in six-month-old 5×FAD mice, as measured by ELISA (see,e.g., FIGS. 59B and 59C, p<0.05 and p<0.01 by Student's t-test, n=13mice per group). Tissue was further treated with guanidine hydrochloricacid (HCl) to extract the insoluble Aβ₁₋₄₀ and Aβ₁₋₄₂ fraction, whichconstitutes aggregated amyloid plaques. Insoluble Aβ₁₋₄₀ and Aβ₁₋₄₂levels were reduced by 43.7% and 57.9% respectively, indicating that40-Hz flicker disrupted the insoluble Aβ aggregates already formed inthe six-month-old mice (see, e.g., FIGS. 59B and 59C, p<0.01 and p<0.001by Student's t-test, n=13 mice per group).

To determine how plaque load, specifically, was affected, in someembodiments, immunohistochemical characterization was performed using anAβ antibody (Cell Signaling Technology; D54D2). FIG. 60A is a series ofimmunofluorescence images illustrating immunohistochemistry with anti-Aβ(D5452) antibody in visual cortices of six-month-old 5×FAD mice afterseven days of one hour/day under dark (top) or 40-Hz flicker (bottom)conditions in accordance with some embodiments (scale bar=50 μm). Aβsignals that appeared intracellular were excluded. FIG. 60B is bar graphdepicting the number of Aβ-positive plaque deposits after seven days ofone hour/day under dark or 40-Hz flicker conditions in visual corticesof six-month-old 5×FAD mice in accordance with some embodiments (n=8mice per group, three asterisks indicate p<0.001, by Student's t-test).FIG. 60C is a bar graph depicting the area of Aβ-positive plaques afterseven days of one hour/day under dark or 40-Hz flicker conditions invisual cortices of six-month-old 5×FAD mice in accordance with someembodiments (n=8 mice per group; two asterisks indicate p<0.01 by MannWhitney test). FIGS. 60B and 60C show mean and SEM.

Plaque abundance was quantified by counting the number of Aβ+ depositsgreater than or equal to about 10 μm in diameter. The 40-Hz flickerreduced the plaque number to 11.0 compared to 33.5 in dark controls(see, e.g., FIGS. 60A and 60B, p<0.01 by Student's t-test, n=8 mice pergroup). In addition, plaque size (measured as the area of the denseplaque region) after one week of 40-Hz flicker treatment, decreased byapproximately 63.7% compared to dark controls (see, e.g., FIGS. 60A and60C, p<0.01 by Mann Whitney test, n=8 mice per group). Taken together,these experiments identified a completely non-invasive treatment with aprofound effect on amyloid plaque pathology.

To determine if 40-Hz flicker improves another key AD-related pathology,tau phosphorylation was investigated using the TauP301S tauopathy mousemodel. Four-month-old TauP301S Tg mice, which show phosphorylated taulocalized to the cell body at this age, were treated with either 40-Hzflicker or dark control conditions for one hour daily for seven days. Toexamine how 40-Hz flicker altered tau phosphorylation,immunohistochemical characterization of the visual cortex was performedusing pTau antibodies against three different epitopes of pTau (S202,S396, and S400/T403/S404; 11834S, 9632S, 11837S) and dendritic markerMAP2 as a control.

FIG. 61A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-pTau 6102 (S202) and anti-MAP2 6104antibodies in four-month-old P301S mice after seven days of one hour/dayunder dark or 40-Hz flicker conditions in accordance with someembodiments. Images were taken with 40× objective (scale bar=50 μm;insets include 100× rendering of representative cell body under dark and40-Hz flicker conditions). FIG. 61B is a bar graph depicting relativepTau (S202) intensity levels of P301S visual cortex after seven days ofone hour/day under dark and 40-Hz flicker conditions in accordance withsome embodiments (n=8 mice per group; one asterisk indicates p<0.05 byStudent's t-test). FIG. 61C is a bar graph depicting relative MAP2intensity levels of P301S visual cortex after seven days of one hour/dayunder dark and 40-Hz flicker conditions in accordance with someembodiments (n=8 mice per group; “n.s.” indicates not significant, byStudent's t-test). FIGS. 61B and 61C show mean and SEM.

FIG. 62A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-pTau 6202(S404) antibodies in 4-month-oldP301S mice after seven days of one hour/day under dark and 40-Hz flickerconditions in accordance with some embodiments (scale bar=50 μm). FIG.62B is a bar graph depicting relative pTau (S400/T403/S404) fluorescenceintensity levels of P301S visual cortex after seven days of one hour/dayunder dark and 40-Hz flicker conditions in accordance with someembodiments (n=8 mice per group; two asterisks indicate p<0.01, byStudent's t-test). FIG. 62B shows mean and SEM.

FIG. 63A is a series of immunofluorescence images illustratingimmunohistochemistry with anti-pTau 6302 (S396) antibodies infour-month-old P301S mice after seven days of one hour/day under darkand 40-Hz flicker conditions in accordance with some embodiments (scalebar=50 μm). FIG. 63B is a bar graph depicting relative pTau (S396)fluorescence intensity levels of P301S visual cortex after seven days ofone hour/day under dark and 40-Hz flicker conditions in accordance withsome embodiments (n=8 mice per group; four asterisks indicate p<0.0001,by Student's t-test).

The results showed that the signal intensity of the pTau(S202) wasreduced by 41.2% and pTau(S400/T403/S404) by 42.3% in the 40-Hz flickerconditions compared to dark controls (see, e.g., FIGS. 61A-B, 62A-B,p<0.01 by Student's t-test, n=2 sections from 8 mice per group), whileMAP2 levels were unchanged (see, e.g., FIGS. 61A and 61C, “n.s.”indicates not significant, n=2 sections from 4 mice per group). Stainingwith an antibody against pTau (S396) showed a trend in the samedirection: 40-Hz flicker reduced pTau (S396) levels by 14.4% compared todark controls (see, e.g., FIGS. 63A-B, “n.s.” indicates not significant,n=2 sections from 8 mice per group). Moreover, less punctate andcell-body localization of pTau signal in response to 40-Hz flickercompared to the dark controls were observed. Although significantchanges in tau phosphorylation were seen, no discernable difference inthe levels of insoluble tau between 40-Hz flicker treated and darkcontrol groups were observed.

The consequence of 40-Hz flicker on microglia in the TauP301S mousemodel was evaluated. FIG. 64 is a series of immunofluorescence imagesillustrating immunohistochemistry with anti-Iba1 (019-19741) antibodiesin four-month-old P301S mice after seven days of one hour/day under darkand 40-Hz flicker conditions in accordance with some embodiments. Imageswere taken with 40× objective (scale bar=50 μm; insets include 100×rendering of representative microglia in EYFP and 40-Hz stimulationconditions).

FIG. 65A is a bar graph depicting the number of microglia after sevendays of one hour/day under dark and 40-Hz flicker conditions inaccordance with some embodiments (n=8 mice per group; “n.s.” indicatesnot significant, by Student's t-test). FIG. 65B is a bar graph depictingthe diameter of microglial cell bodies normalized to control after sevendays of one hour/day under dark and 40-Hz flicker conditions inaccordance with some embodiments (n=8 mice per group; four asterisksindicate p<0.0001 by Student's t-test). FIG. 65C is a bar graphdepicting the average length of microglia primary processes normalizedto control after seven days of one hour/day under dark and 40-Hz flickerconditions in accordance with some embodiments (n=8 mice per group; fourasterisks indicate p<0.0001 by Student's t-test).

In some embodiments, microglia with an anti-Iba1 antibody in visualcortex sections of the TauP301S mouse was labeled following seven daysof one hour daily 40-Hz flicker or dark conditions (see, e.g., FIG. 64).In some embodiments, a trend was observed towards a 29.50% increase inmicroglia number in 40-Hz flicker conditions compared to dark controls(see, e.g., FIGS. 64 and 65A, “n.s.” indicates not significant, n=3 miceper group) consistent with observations made in the 5×FAD model (see,e.g., FIG. 50A). In addition, the microglial cell body diameterincreased by 49.00% following 40-Hz flicker in the visual cortexcompared to dark controls (see, e.g., FIGS. 64 and 65B, p<0.0001 byStudent's t-test, n=3 mice per group). The length of microglia primaryprocesses was reduced by 39.08% in 40-Hz flicker group compared to darkcontrols (see, e.g., FIGS. 64 and 65C, p<0.0001 by Student's t-test, n=3mice per group).

Taken together these data, from multiple models of AD pathology and inWT animals, demonstrate that 40-Hz oscillations may mitigate amyloidpathology, as measured by a reduction in Aβ levels, and may reduce tauphosphorylation. Furthermore, 40 Hz visual flicker may drive a distinctmorphological transformation of microglia in both amyloidosis andtauopathy models of AD pathology.

In another experiment, a subset of aged mice (i.e., six months old) wereexposed to visual gamma stimulation for seven days. The remaining micewere kept in the dark. FIG. 66 is a plot illustrating the levels of bothsoluble Aβ peptide and insoluble Aβ peptide (i.e., plaques) in thevisual cortex of the mice. As shown in FIG. 66, the levels of each ofsoluble isoform Aβ₁₋₄₀ 6600, soluble isoform Aβ₁₋₄₂ 6602, insolubleisoform Aβ₁₋₄₀ 6604, and insoluble isoform Aβ₁₋₄₂ 6606 weresignificantly reduced in the mice exposed to the visual gammastimulation.

FIGS. 67A-67B are plots illustrating Aβ peptide levels with and withouttranscranial gamma stimulation of a subject in accordance with someembodiments. In FIG. 67A, whole brain Aβ peptide levels stayed the samewith no stimulation 6700 but fell following one hour of transcranialgamma stimulation 6702 (n=1 animal per group). In FIG. 67B, whole brainAβ peptide levels were reduced following 40z transcranial stimulation atthe hippocampus 6704 and at the cortex 6706 of a 5×FAD mouse inaccordance with some embodiments.

Gamma oscillations have long been thought to be associated with highercognitive functions and sensory responses. In some embodiments, drivingFS-PV-interneurons using optogenetic methods enhanced LFPs at 40 Hz inmice. As disclosed herein, it has been demonstrated that in someembodiments, driving 40-Hz oscillations and phase locked spiking, usingoptogenetics or a non-invasive light flickering treatment in the 5×FADmouse model, resulted in marked reduction of Aβ peptides in at least twodifferent brain regions. This reduction was not due to decreased spikingactivity because Aβ peptide levels were significantly lower in responseto 40-Hz stimulation than to a random stimulation condition thatproduced similar amounts of multi-unit spiking activity withoutenhancing 40-Hz oscillations. Pyramidal cell firing rates may differbetween these conditions but firing of FS-PV-interneurons or other celltypes masked this change. In some embodiments, random optogeneticstimulation of FS-PV-interneurons provided the same amount of directstimulation of FS-PV-interneurons yet did not reduce amyloid. In fact,optogenetic stochastic stimulation more than tripled amyloid levelswhile stochastic visual flicker produced no significant change, whichmay indicate that some aspects of the random stimulation have neurotoxiceffects. While in some embodiments, random stimulation did not result inincreased gamma power, a trend of small increases in power was noticedin a wide range of frequencies, from around 20 Hz to greater than 60 Hz.In some embodiments, a trend for increased amyloid levels with 20-Hz and80-Hz light flicker was noticed. Taken together, these results maysuggest that driving activity at some frequencies below or above 40 Hzmay increase amyloid levels. These results point to a need to understandhow patterns of spiking activity affect molecular pathways and diseasepathology.

The robust reduction of total amyloid levels is likely mediated by bothdecreased amyloidogenesis, involving reduced EEA1/Rab5-positive earlyendosomes, and increased endocytosis of amyloid by microglia.Importantly, Gene Set Enrichment Analysis (GSEA) statistical analysis(The Broad Institute, Cambridge, Mass.) disclosed herein showed that theclassical macrophage pro-inflammatory M1 or anti-inflammatory M2cellular state did not correlate with either up- or down-regulated geneexpression profiles following neuronal stimulation by 40-Hzoscillations. Indeed, the expression levels of pro-inflammatory genesIl6, II1b, Itgam and anti-inflammatory gene Igf1 were not changed afterstimulation. Instead, a number of microglia pro-phagocytic genes as wellas cell adhesion/migration regulator Spp1 were activated upon 40-Hzstimulation. Thus, it appears that driving 40 Hz gamma oscillationsinduces an overall neuroprotective response by recruiting both neuronsand microglia. The fact that GABA-A antagonist treatment completelyabrogated the effects of 40-Hz stimulation on reducing Aβ levelsstrongly suggests that GABAergic signaling, most likely involvingFS-PV-interneurons, is critical for those effects. Furthermore, in someembodiments, 40-Hz flicker stimulation reduced Aβ in multiple mousemodels including APP/PS1 and WT mice in addition to the 5×FAD mouse.This replication in multiple mouse models shows that these findings maynot be specific to one animal model and, importantly, may extend tosituations where APP is expressed by its physiological promoter and Aβis generated from endogenous APP as in the WT animals. In addition, insome embodiments, it was found that 40-Hz oscillations reduced pTau in amouse model of tauopathy, TauP301S, showing that the protective effectsof gamma stimulation generalize not only to other mouse models but alsoto other pathogenic proteins. In summary, the findings disclosed hereinuncover previously unknown cellular and molecular processes mediated bygamma oscillations and establish a functional connection between braingamma rhythms, microglia function, and AD-related pathology. In someembodiments, the findings of deficits in gamma oscillations convergewith evidence of gamma deficits in different mouse models of AD (hAPPand apoE4) and reports that gamma is altered in humans with AD. Byseeking converging evidence from multiple mouse models of AD, includingTg and knock-in models, it may be demonstrated that these results arenot due solely to overexpression of transgenes or to other side effectsparticular to one model. Together these results from mice and humansshow that multiple molecular pathways that contribute to Aβ pathologyconverge to alter gamma oscillations in AD. The findings disclosedherein hold promise for a novel therapeutic intervention against AD.

One theory of AD pathogenesis points to microglia malfunction,specifically microglia's failure to clear out pathological molecules, asa key mechanism of disease progression. Therefore, interventions thatrecruit microglia back to an endocytotic state, as 40-Hz stimulationdoes, have strong therapeutic potential. In the experiments describedfurther herein, driving gamma oscillations optogenetically or via lightflicker did not cause neuronal hyperactivity. Because this approach isfundamentally different from prior AD therapies, driving such patternedneural activity to trigger endogenous repair would provide a noveltherapeutic approach to AD.

Visual Stimulation at Gamma Frequency Had Positive Effects on SubjectBehavior.

A study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments causes any stress toa subject. FIG. 68A is a flow diagram illustrating the study. As shownat 6800 in FIG. 68A, WT mice were exposed to either normal room light(N=8) or a 40-Hz light flicker (N=8) in accordance with some embodimentsfor one hour per day for seven consecutive days, Days 1-7. On Day 8,shown at 6802, blood was collected from the mice, and the blood plasmawas separated to examine corticosterone levels. In mice, corticosteroneis a main glucocorticoid involved in stress responses.

FIG. 68B is a bar graph depicting levels (pg/ml) of corticosterone(CORT) in the plasma collected from the eight mice exposed to normalroom light (NRL) and the eight mice exposed to the 40-Hz light flicker(40-Hz). No increase in corticosterone was observed in the mice exposedto the 40-Hz light flicker. Instead, the group of mice exposed to the40-Hz light flicker had lower levels of corticosterone compared to thecontrol group. For N=8 independent measures per group, theT-distribution and the p-value for corticosterone levels were calculatedto be:

T(14)=0.827;p=0.422  (1)

Another study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments reduces anxiety in asubject. FIG. 69A is a flow diagram illustrating the study. As shown at6900 in FIG. 69A, WT mice were exposed to either normal room light(N=10) or a 40-Hz light flicker (N=10) in accordance with someembodiments for one hour per day for seven consecutive days, Days 1-7.On Day 8, shown at 6902, a ten-minute session of elevated plus maze wasconducted.

The elevated plus maze is a test used to measure anxiety in laboratoryanimals. The behavioral model is based on the general aversion ofrodents to open spaces, which leads to thigmotaxis, a preference forremaining in enclosed spaces or close to the edges of a bounded space.FIG. 69B is an image illustrating an elevated plus maze apparatus. Theapparatus is plus-shaped with two open arms (vertical) and two enclosedarms (horizontal). Anxiety is expressed by the animal spending more timein the enclosed arms.

FIGS. 69C and 69D are images illustrating representative tracks of thesubjects during the elevated plus maze session. In FIG. 69C, a mouseexposed to normal room light tended to stay in the enclosed arms,indicating more anxiety, whereas in FIG. 69D, a mouse exposed to the40-Hz light flicker explored in both the open arms and enclosed arms,indicating relatively less anxiety in accordance with some embodiments.

FIG. 70 is a bar graph depicting total time spent exploring in open armsand closed arms by the ten mice exposed to normal room light (NRL) andthe ten mice exposed to the 40-Hz light flicker (40-Hz) in accordancewith some embodiments. The mice exposed to the 40-Hz light flicker spentless total time in the closed arms and more total time in the open arms,indicating less anxiety compared to the control group in accordance withsome embodiments. For N=10 independent measures per group, theT-distribution and the p-value for total time spent exploring the closedarms were calculated to be:

T(18)=−1.652;p=0.11  (2)

For N=10 independent measures per group, the T-distribution and thep-value for total time spent exploring the open arms were calculated tobe:

T(18)=−2.136;p=0.047  (3)

Another study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments reduces stress and/oranxiety in a subject. FIG. 71A is a flow diagram illustrating the study.At 7100 in FIG. 71A, WT mice were exposed to either normal room light(N=8) or a 40-Hz light flicker (N=8) in accordance with some embodimentsfor one hour per day for seven consecutive days, Days 1-7. On Day 8,shown at 7102, a five-minute open field test was conducted.

The open field test is an experiment used to assay general locomotoractivity levels and anxiety in laboratory animals. The behavioral modelis based on anxiety caused by the conflicting drives of rodents to avoidbrightly lit areas but also explore a perceived threatening stimulus.FIG. 71B is an image illustrating an open field arena. The open fieldarena has walls to prevent escape and may be marked with a grid ormonitored using infrared beams or video cameras integrated with softwaresystems. Increased anxiety will result in less locomotor motion andpreference for the edges of the field, whereas decreased anxiety leadsto increased exploratory behavior in accordance with some embodiments.

FIGS. 71C and 71D are images illustrating representative tracks of thesubjects during the open field test. In FIG. 71C, a mouse exposed tonormal room light tended to prefer the edges of the arena, indicatingmore stress and/or anxiety, whereas in FIG. 71D, a mouse exposed to the40-Hz light flicker explored more in the center of arena, indicatingrelatively less stress and/or anxiety in accordance with someembodiments.

FIGS. 72A and 72B are graphs depicting total time spent exploring thecenter and the periphery of the open field arena by the eight miceexposed to normal room light (NRL) and the eight mice exposed to the40-Hz light flicker (40-Hz) in accordance with some embodiments. FIG.72A is a plot of the average amounts of seconds spent in the center ofthe arena for each of the five minutes. FIG. 72B is a bar graph of thetotal time spent in the periphery of the arena for the entirefive-minute duration, averaged for each minute.

On average, the mice exposed to the 40-Hz light flicker spent more timein the center of the arena, significantly so during Minutes 2, 4, and 5,thus indicating less stress and/or anxiety compared to the controlgroup, which also is consistent with the elevated plus maze results inaccordance with some embodiments. Repeated measures analysis of variance(RM ANOVA) was performed. For N=8 independent measures per group, theF-distribution and the p-value for mean times spent exploring the openfield arena were calculated to be:

F(1,14)=4.860;p=0.045  (4)

Another study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments alters innate noveltyseeking behavior in a subject. FIGS. 73A and 73B are schematic diagramsillustrating the study using a novel recognition task. In FIG. 73A, twonovel objects are provided in a familiar arena. In FIG. 73B, onefamiliar object and one novel object are provided in the familiar arena.Wild type mice were exposed to either normal room light (N=8) or a 40-Hzlight flicker (N=8) in accordance with some embodiments for one hour perday for seven consecutive days, Days 1-7.

On Day 8, the mice were exposed to the scenario in FIG. 73A, two novelobjects in a familiar arena, for five minutes. FIG. 73C is a bar graphdepicting the percentage of time spent exploring new object A to thepercentage of time spent exploring new object B for the eight miceexposed to normal room light (NRL) and the eight mice exposed to the40-Hz light flicker (40-Hz) in accordance with some embodiments. Asillustrated by FIG. 73C, equal preference was shown to each object byeach group. That is, no difference was observed in the objectexploration between the groups.

Then, the mice were exposed to the scenario in FIG. 73B, one familiarobject and one novel object in the familiar arena, for five minutes.FIG. 74 is a plot depicting the average amounts of seconds spentexploring the novel object for each of the five minutes. On average, themice exposed to the 40-Hz light flicker spent significantly higheramounts of time exploring the novel object, especially during Minutes1-3 and 5, thus indicating increased novelty seeking behavior comparedto the control group in accordance with some embodiments. Friedman'snon-parametric RM ANOVA was performed. For N=8 independent measures pergroup, the test statistic χ² and the p-value for mean times spentexploring the novel object were calculated to be:

χ²(4,n=16)=16.088;p=0.003  (5)

The Mann-Whitney U test was performed for mean times spent exploring thenovel object during Minute 3. For N=8 independent measures per group,the U-value, the Z-value, and the p-value were calculated to be:

U=58.00;Z=2.731;p=0.005  (6)

Another study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments impacts learning andmemory in a subject. FIG. 75A is a flow diagram illustrating the studyusing a fear conditioning paradigm. As shown at 7500 in FIG. 75A, WTmice were exposed to either normal room light or a 40-Hz light flickerin accordance with some embodiments for one hour per day for sevenconsecutive days, Days 1-7. On Day 8, shown at 7502, the mice weresubjected to a mild two-tone-shock pairing. Specifically, the mice wereintroduced into a new arena in which a first tone was paired with a footshock. The mice became conditioned to associate a context (i.e., tone)with an aversive experience (i.e., foot shock). For this originalcontext, the T-distribution and the p-value for total time spentfreezing were calculated to be:

T(24)=0.577;p=0.569  (7)

On Day 9, shown at 7504, a tone test was conducted in an alteredcontext. FIG. 75B is a stimulus diagram illustrating the tone test as afunction of time, including a first-tone context 7506, a post-first-tonecontext 7508, a second-tone context 7510, and a post-second-tone context7512. For the test, the mice were returned to the arena in which thefirst tone was paired with the foot shock. When the first-tone context7506 was applied, the mice exposed to the 40-Hz light flicker spent moretime freezing, presumably in anticipation of the foot shock, thusindicating a measure of memory. The mice exposed to the 40-Hz lightflicker also spent more time freezing during the second-tone context7510 than the control group, but less time freezing during eitherpost-tonal context.

FIGS. 76A and 76B are bar graphs demonstrating enhanced memory inaccordance with some embodiments. As shown in FIG. 76A, the percentagesof time spent freezing during the first-tone context 7506 and thesecond-tone context 7510 were greater for the mice exposed to the 40-Hzlight flicker compared to the control group, indicating enhanced memoryassociation in accordance with some embodiments. In addition, the miceexposed to the 40-Hz light flicker exhibited stronger extinctionpost-tone presentation in accordance with some embodiments. As shown inFIG. 76B, the percentages of time spent freezing during thepost-first-tone context 7506 and the post-second-tone context 7510 weregreater for the control group compared to the mice exposed to the 40-Hzlight flicker, indicating enhanced memory specificity in accordance withsome embodiments.

For the pre-tonal context, RM ANOVA was performed between groups and theF-distribution and the p-value for mean times spent freezing werecalculated to be:

F(1,24)=3.106;p=0.091  (8)

For the first-tone context, the T-distribution and the p-value for totaltime spent freezing were calculated to be:

T(24)=−2.155;p=0.041  (9)

For the second-tone context, the T-distribution and the p-value fortotal time spent freezing were calculated to be:

T(24)=−1.433;p=0.164  (10)

For the tone contexts, RM ANOVA was performed between groups and theF-distribution and the p-value for mean times spent freezing werecalculated to be:

F(1,24)=4.559;p=0.043  (11)

For the post-first-tone context, the T-distribution and the p-value fortotal time spent freezing were calculated to be:

T(24)=1.874;p=0.073  (12)

For the post-second-tone context, the T-distribution and the p-value fortotal time spent freezing were calculated to be:

T(24)=2.223;p=0.036  (13)

For the post-tonal contexts, RM ANOVA was performed between groups andthe F-distribution and the p-value for mean times spent freezing werecalculated to be:

F(1,24)=6.646;p=0.017  (14)

Another study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments improves memory in asubject. FIG. 77A is a flow diagram illustrating the study. As shown at7700 in FIG. 77A, WT mice were exposed to either normal room light or a40-Hz light flicker in accordance with some embodiments for one hour perday for seven consecutive days, Days 1-7. On Day 8, shown at 7702, aMorris water maze test was conducted.

The Morris water navigation task or maze is a test used to study spatialmemory and learning in laboratory animals. The behavioral procedureinvolves placing a subject in a large circular pool with an invisible orvisible platform that allows the subject to escape the water using apraxic strategy (remembering movements required to reach the platform),a taxic strategy (using visual cues to locate the platform), or aspatial strategy (using distal cues as points of reference). FIG. 77B isa diagram illustrating a Morris water maze. The maze includes a circularpool of water divided into directional quadrants and a platform 7704hidden in the South-West (SW) quadrant.

For weak training, the Morris water maze test was repeated twice per dayfor four consecutive days, Days 8-11. FIG. 78A is a plot depictinglatency to find the platform by the mice exposed to normal room light(NRL) and the mice exposed to the 40-Hz light flicker (40-Hz) inaccordance with some embodiments.

On Day 12, a probe test was conducted by removing the hidden platformfrom the Morris water maze. FIGS. 77C and 77D are images illustratingrepresentative tracks of the subjects during the probe test. In FIG.77C, a mouse exposed to normal room light appears to have searched forthe platform throughout the pool, whereas in FIG. 77D, a mouse exposedto the 40-Hz light flicker appears to have searched more methodicallyand primarily in the SW quadrant in accordance with some embodiments.FIG. 78B is a plot depicting the total time (seconds per each halfminute) spent searching for the platform in the target quadrant (i.e.,the SW quadrant), whereas FIG. 78C is a plot depicting the total time(seconds per each half minute) spent searching for the platform in theopposite quadrant (i.e., the NE quadrant). The mice exposed to the 40-Hzlight flicker spent more time than the control group searching in thetarget quadrant and less time than the control group searching in theopposite quadrant, indicating enhancement of spatial memory inaccordance with some embodiments.

Reversal learning was conducted using the same groups of mice from theMorris water maze trials and probe test. FIG. 79A is a diagramillustrating a Morris water maze with a platform 7900 hidden in the SWquadrant as in the trials. FIG. 79B is a diagram illustrating a Morriswater maze with a platform 7902 hidden in the opposite NE quadrant forreversal learning.

For weak training, reversal learning was repeated twice per day for fourconsecutive days, Days 14-17. FIG. 79C is a plot depicting latency tofind the platform by the mice exposed to normal room light (NRL) and themice exposed to the 40-Hz light flicker (40-Hz) in accordance with someembodiments. Despite receiving no further 40-Hz exposure after Day 7,the mice exposed to the 40-Hz light flicker showed increased behavioralflexibility.

Another study was conducted to examine whether chronic gamma exposureand/or administration in accordance with some embodiments influencesspatial learning and memory in a subject. FIG. 80A is a flow diagramillustrating the study. As shown at 8000 in FIG. 80A, C57BL/6 mice wereexposed to either normal room light (N=7) or a 40-Hz light flicker (N=7)in accordance with some embodiments for one hour per day for two weeks.During the third week, shown at 8002, the mice continued to be exposedto either normal room light or a 40-Hz light flicker for one hour eachmorning and then also subjected to a Morris water maze test eachafternoon.

FIG. 80B is a plot depicting the latency to find the platform by themice exposed to normal room light (NRL) and the mice exposed to the40-Hz light flicker (40-Hz) on Days 1-4 of the third week. Following thethird week, a probe test was conducted by removing the hidden platform.FIG. 80C is a bar graph depicting the total time (seconds per 30-secondtrial) spent searching for the platform in the target quadrant duringthe probe test. Similar to one week of treatment, chronic three weektreatment enhanced spatial learning in accordance with some embodiments.

Reversal learning was conducted using the same groups of mice from FIGS.80A-80C. FIG. 81A is a flow diagram illustrating the expanded study. Asshown at 8100 in FIG. 81A, the C57BL/6 mice were exposed to eithernormal room light or a 40-Hz light flicker in accordance with someembodiments for one hour per day for two weeks. During the third week,shown at 8102, the mice continued to be exposed to either normal roomlight or a 40-Hz light flicker for one hour each morning and then alsosubjected to a Morris water maze test each afternoon. During the fourthweek, shown at 8104, the mice continued to be exposed to either normalroom light or a 40-Hz light flicker for one hour each morning and thenalso subjected to a Morris water maze reversal test each afternoon. FIG.81B is a plot depicting the latency to find the platform by the miceexposed to normal room light (NRL) and the mice exposed to the 40-Hzlight flicker (40-Hz) on Days 1-4 of the fourth week in accordance withsome embodiments.

Following the fourth week, a probe test was conducted by removing thehidden platform. FIG. 82A is a bar graph depicting the total time(seconds per 30-second trial) spent searching for the platform in thetarget quadrant during the probe test. FIG. 82B is a bar graph depictingthe time spent in the opposite quadrant during the probe test. The miceexposed to the 40-Hz light flicker showed strong cognitive flexibility.

Visual Stimulation at Gamma Frequency Provided Anatomical, Morphology,Cellular, and Molecular Benefits.

A study was conducted to examine the effect of gamma exposure and/oradministration in accordance with some embodiments on DNA damage andneuronal loss in the visual cortex of a subject. For the study, aninducible mouse model of p25 accumulation (i.e., a creatine kinasecarboxyl-terminal fragment p25 Tg mouse (CK-p25 Tg mouse)) was used. TheCK-p25 Tg mouse model displays key pathological hallmarks of AD,including profound neuronal loss in the forebrain, increased Aβ peptideproduction, tau pathology, DNA damage, and severe cognitive impairment.In this model, increased Aβ peptide levels are observed prior toneuronal loss; furthermore, reducing Aβ peptide production amelioratesmemory deficits in the CK-p25 Tg mouse model, indicating that this eventoperates synergistically with the carboxyl-terminal fragment p25,leading to the manifestation of neurodegeneration and memory impairment.

FIG. 83 is a timeline diagram 8300 illustrating changes in CK-p25 Tgmice. After two weeks 8302, the mice exhibit DNA damage (e.g., biomarkerγH2AX), increased Aβ peptide, and microglia activation. After six weeks8304, the mice exhibit synaptic loss, neuronal loss, tauhyper-phosphorylation, long-term potentiation deficits, and memoryimpairment.

A study was conducted to compare groups of mice under differenttreatment regimens. FIG. 84 is a diagram of the groups includingCK-control mice 8400, untreated CK-p25 Tg mice 8402, CK-p25 Tg micetreated with memantine (10 mg/kg daily) 8404, CK-p25 Tg mice exposed tothe 40-Hz light flicker (one hour daily for 6 weeks) in accordance withsome embodiments 8406, and CK-p25 Tg mice treated with memantine andalso exposed to the 40-Hz light flicker 8408. Memantine is a medicationused with limited success to treat severe AD by blocking NMDA receptors,thereby acting on the glutamatergic system.

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to brain anatomy. Forexample, gamma exposure reduced and/or prevented CKp-25-induced loss ofbrain weight. FIG. 85 is bar graph comparing brain weight change inCK-control mice, untreated CK-p25 Tg mice, CK-p25 Tg mice treated withmemantine, CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Brain weight loss was pronouncedin untreated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, andCK-p25 Tg mice treated with both memantine and the 40-Hz light flicker.However, CK-p25 Tg mice exposed to the 40-Hz light flicker in accordancewith some embodiments retained more brain weight.

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to brain morphology. Forexample, gamma exposure reduced and/or prevented CKp-25-induced abnormallateral ventricle expansion in subjects. FIG. 86 is bar graph comparingfold change of lateral ventricle expansion in CK-control mice, untreatedCK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg miceexposed to the 40-Hz light flicker in accordance with some embodiments,and CK-p25 Tg mice treated with both memantine and the 40-Hz lightflicker with expansion in the CK-control mice as a baseline. Lateralventricle expansion was pronounced in untreated CK-p25 Tg mice, CK-p25Tg mice treated with memantine, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Lateral ventricles in CK-p25 Tgmice exposed to the 40-Hz light flicker in accordance with someembodiments expanded much less than the lateral ventricles in the otherCK-p25 Tg mice.

FIGS. 87A-87E are images illustrating lateral ventricles representativeof subjects in each group. The lateral ventricles were largest inuntreated CK-p25 Tg mice (FIG. 87A), CK-p25 Tg mice treated withmemantine (FIG. 87B), and CK-p25 Tg mice treated with both memantine andthe 40-Hz light flicker (FIG. 87C). As shown in FIG. 87D, the lateralventricles of CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments expanded much less. FIG. 87E is anexample of the baseline lateral ventricle size in CK-control mice.

FIGS. 88A-88C are brain anatomy diagrams illustrating brain regions ofinterest for molecular characterization in accordance with someembodiments. FIG. 88A includes the visual cortex (V1) 8800, thesomatosensory cortex (SS1) 8802, the hippocampus 8804, and the insularcortex 8806.

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to cortical and neuronallayers in the visual cortex. For example, gamma exposure reduced and/orprevented CKp-25-induced cortical and neuronal layer loss in the visualcortex of subjects.

Cortical layer loss was gauged using nuclear staining with Hoechstlabels (i.e., blue fluorescent dyes used to stain DNA). Neuronal layerloss was gauged using NeuN, a neuronal nuclear antigen that is commonlyused as a biomarker for neurons. FIG. 89 is a bar graph depictingaverage thickness of the V1-cortical layer in each group, and FIG. 90 isa bar graph depicting average thickness of the V1-NeuN-positive celllayer in each group.

FIGS. 91A-91E are images illustrating cells with Hoechst labels and/orNeuN labels representative of subjects in each group. FIG. 91A is anexample of the thickness of the baseline V1-cortical layer (e.g., 837±9μM) and V1-neuronal layer (e.g., 725±7 μM) in CK-control mice.

The V1-cortical layers were progressively thinner in CK-p25 Tg miceexposed to the 40-Hz light flicker in accordance with some embodiments(FIG. 91D, e.g., 855±9 μM); CK-p25 Tg mice treated with both memantineand the 40-Hz light flicker (FIG. 91E, e.g., 821±22 μM); untreatedCK-p25 Tg mice (FIG. 91B, e.g., 792±13 μM); and CK-p25 Tg mice treatedwith memantine (FIG. 91C, e.g., 788±9 μM).

The V1-neuronal layers in CK-p25 Tg mice exposed to the 40-Hz lightflicker in accordance with some embodiments were actually thicker thanin the CK-control mice (FIG. 91D, e.g., 743±9 but then progressivelythinner than in the CK-control mice in CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker (FIG. 91E, e.g., 691±20 μM);untreated CK-p25 Tg mice (FIG. 91B, e.g., 666±14 μM); and CK-p25 Tg micetreated with memantine (FIG. 91C, e.g., 660±7 μM).

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to cortical and neuronallayers in the somatosensory cortex. For example, gamma exposure reducedand/or prevented CKp-25-induced cortical and neuronal layer loss in thesomatosensory cortex of subjects.

FIG. 92 is a bar graph depicting average thickness of the SS1-corticallayer in each group, and FIG. 93 is a bar graph depicting averagethickness of the SS1-NeuN-positive cell layer in each group.

FIGS. 94A-94E are images illustrating cells with Hoechst labels and/orNeuN labels representative of subjects in each group. FIG. 94A is anexample of the thickness of the baseline SS1-cortical layer (e.g.,846±10 μM) and SS1-neuronal layer (e.g., 707±8 μM) in CK-control mice.

The SS1-cortical layers were progressively thinner in CK-p25 Tg miceexposed to the 40-Hz light flicker in accordance with some embodiments(FIG. 94D, e.g., 834±9 μM); CK-p25 Tg mice treated with both memantineand the 40-Hz light flicker (FIG. 94E, e.g., 778±13 μM); untreatedCK-p25 Tg mice (FIG. 94B, e.g., 762±17 μM); and CK-p25 Tg mice treatedwith memantine (FIG. 94C, e.g., 756±11 μM).

The SS1-neuronal layers in CK-p25 Tg mice exposed to the 40-Hz lightflicker in accordance with some embodiments were nearly the samethickness as that in the CK-control mice (FIG. 94D, e.g., 705±15However, the SS1-neuronal layers were progressively thinner in CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker (FIG. 94E,e.g., 650±11 μM); untreated CK-p25 Tg mice (FIG. 94B, e.g., 630±13 μM);and CK-p25 Tg mice treated with memantine (FIG. 94C, e.g., 629±9 μM).

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to cortical and neuronallayers in the insular cortex. For example, gamma exposure reduced and/orprevented CKp-25-induced cortical and neuronal layer loss in the insularcortex of subjects.

FIG. 95 is a bar graph depicting average thickness of the cortical layerof the insular cortex in each group, and FIG. 96 is a bar graphdepicting average thickness of the NeuN-positive cell layer of theinsular cortex in each group.

FIGS. 97A-97E are images illustrating cells with Hoechst labels and/orNeuN labels representative of subjects in each group. FIG. 97A is anexample of the thickness of the baseline cortical layer (e.g., 1134±10μM) and neuronal layer (e.g., 1010±11 μM) of the insular cortex inCK-control mice.

The cortical layers were progressively thinner in the insular corticesof CK-p25 Tg mice exposed to the 40-Hz light flicker in accordance withsome embodiments (FIG. 97D, e.g., 1079±20 μM); CK-p25 Tg mice treatedwith memantine (FIG. 97C, e.g., 983±12 μM); CK-p25 Tg mice treated withboth memantine and the 40-Hz light flicker (FIG. 97E, e.g., 965±16 μM);and untreated CK-p25 Tg mice (FIG. 97B, e.g., 764±27 μM).

The neuronal layers were progressively thinner in the insular corticesof CK-p25 Tg mice exposed to the 40-Hz light flicker in accordance withsome embodiments (FIG. 97D, e.g., 953±17 μM); untreated CK-p25 Tg mice(FIG. 97B, e.g., 861±30 μM); CK-p25 Tg mice treated with memantine (FIG.97C, e.g., 850±18 μM); and CK-p25 Tg mice treated with both memantineand the 40-Hz light flicker (FIG. 97E, e.g., 848±15 μM).

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve and/or reduce changes to the number of neuronsand/or damage of DNA. For example, gamma exposure reduced CKp-25-inducedneuron loss and DNA damage in the visual cortex of subjects.

FIG. 98 is a bar graph comparing the amount of NeuN-positive cells as apercentage of the NeuN-positive cells in CK-control mice for theCK-control mice, untreated CK-p25 Tg mice, CK-p25 Tg mice treated withmemantine, CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Thus, the percentage of theCK-control mice NeuN-positive cells are 100% in the CK-control mice, butonly about 80% in untreated CK-p25 Tg mice, corroborating neuronal lossin the CK-p25 Tg mouse model. Treatment with memantine prevented someneuronal loss in CK-p25 Tg mice compared to the untreated group.Exposure to the 40-Hz light flicker in accordance with some embodimentsprevented most neuronal loss in CK-p25 Tg mice. Thus, FIG. 98illustrates how 40-Hz visual flicker treatment in accordance with someembodiments can preserve neurons in the visual cortex. However,combination of memantine and exposure to the 40-Hz light flicker failedto prevent as much neuronal loss.

DNA double strand breaks (DSB) are one example of DNA damage ineukaryotic cells, causing genomic instability, leading to tumorigenesisand possibly accelerated aging. Phosphorylated histone H2AX (γH2AX) wasused as a biomarker of cellular response to DSB. FIG. 99 is bar graphcomparing the amount of γH2AX-positive cells in CK-control mice,untreated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25Tg mice exposed to the 40-Hz light flicker in accordance with someembodiments, and CK-p25 Tg mice treated with both memantine and the40-Hz light flicker. Cells positive for γH2AX were almost non-existentin CK-control mice, but very high in untreated CK-p25 Tg mice,indicating high amounts of DSB and other DNA damage. Treatment withmemantine reduced the amount of γH2AX-positive cells in CK-p25 Tg micecompared to the untreated group. Exposure to the 40-Hz light flicker inaccordance with some embodiments resulted in even greater reductions ofγH2AX-positive cells in CK-p25 Tg mice. Thus, FIG. 99 illustrates how40-Hz visual flicker treatment in accordance with some embodiments canreduce DNA damage in the visual cortex. However, combination ofmemantine and exposure to the 40-Hz light flicker significantlyincreased the number of γH2AX-positive cells in CK-p25 Tg mice.

FIG. 100 is a series of images illustrating visual cortex samplesrepresentative of subjects in each group labeled with Hoechst stain(indicating cortical cells), green fluorescent protein or GFP(indicating CK-p25), γH2AX (indicating DSB), or NeuN (indicatingneurons).

Gamma exposure also reduced CKp-25-induced neuron loss and DNA damage inthe somatosensory cortex of subjects. FIG. 101 is a bar graph comparingthe amount of NeuN-positive cells as a percentage of the NeuN-positivecells in CK-control mice for the CK-control mice, untreated CK-p25 Tgmice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed tothe 40-Hz light flicker in accordance with some embodiments, and CK-p25Tg mice treated with both memantine and the 40-Hz light flicker. Thus,the percentage of the CK-control mice NeuN-positive cells are 100% inthe CK-control mice, but closer to 80% in untreated CK-p25 Tg mice,corroborating neuronal loss in the CK-p25 Tg mouse model. Treatment withmemantine failed to prevent any neuronal loss in CK-p25 Tg mice comparedto the untreated group except for in combination with exposure to the40-Hz light flicker, which prevented most neuronal loss in CK-p25 Tgmice. Thus, FIG. 101 illustrates how 40-Hz visual flicker treatment inaccordance with some embodiments can preserve neurons in thesomatosensory cortex.

FIG. 102 is bar graph comparing the amount of γH2AX-positive cells inCK-control mice, untreated CK-p25 Tg mice, CK-p25 Tg mice treated withmemantine, CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Cells positive for γH2AX werenon-existent in CK-control mice, but very high in untreated CK-p25 Tgmice, indicating high amounts of DSB and other DNA damage. Treatmentwith memantine reduced the amount of γH2AX-positive cells in CK-p25 Tgmice compared to the untreated group. Exposure to the 40-Hz lightflicker in accordance with some embodiments resulted in even greaterreductions of γH2AX-positive cells in CK-p25 Tg mice. Thus, FIG. 102illustrates how 40-Hz visual flicker treatment in accordance with someembodiments can reduce DNA damage in the somatosensory cortex. However,combination of memantine and exposure to the 40-Hz light flickersignificantly increased the number of γH2AX-positive cells in CK-p25 Tgmice.

FIG. 103 is a series of images illustrating somatosensory cortex samplesrepresentative of subjects in each group labeled with NeuN (indicatingneurons), γH2AX (indicating DSB), GFP (indicating CK-p25), and/orHoechst stain (indicating cortical cells).

Gamma exposure also reduced CKp-25-induced neuron loss and DNA damage inthe insular cortex of subjects. FIG. 104 is a bar graph comparing theamount of NeuN-positive cells as a percentage of the NeuN-positive cellsin CK-control mice for the CK-control mice, untreated CK-p25 Tg mice,CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to the40-Hz light flicker in accordance with some embodiments, and CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker. Thus, thepercentage of the CK-control mice NeuN-positive cells are 100% in theCK-control mice, but closer to 80% in untreated CK-p25 Tg mice,corroborating neuronal loss in the CK-p25 Tg mouse model. Treatment withmemantine prevented some neuronal loss in CK-p25 Tg mice compared to theuntreated group except for in combination with exposure to the 40-Hzlight flicker, which prevented the least neuronal loss in CK-p25 Tgmice. Thus, FIG. 104 illustrates how 40-Hz visual flicker treatment inaccordance with some embodiments can preserve neurons in the insularcortex.

FIG. 105 is bar graph comparing the amount of γH2AX-positive cells inCK-control mice, untreated CK-p25 Tg mice, CK-p25 Tg mice treated withmemantine, CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Cells positive for γH2AX werenon-existent in CK-control mice, but very high in untreated CK-p25 Tgmice, indicating high amounts of DSB and other DNA damage. Treatmentwith memantine reduced the amount of γH2AX-positive cells in CK-p25 Tgmice compared to the untreated group. Exposure to the 40-Hz lightflicker in accordance with some embodiments resulted in similarreductions of γH2AX-positive cells in CK-p25 Tg mice. Thus, FIG. 105illustrates how 40-Hz visual flicker treatment in accordance with someembodiments can reduce DNA damage in the insular cortex. However,combination of memantine and exposure to the 40-Hz light flickersignificantly increased the number of γH2AX-positive cells in CK-p25 Tgmice.

FIG. 106 is a series of images illustrating insular cortex samplesrepresentative of subjects in each group labeled with NeuN (indicatingneurons), γH2AX (indicating DSB), GFP (indicating CK-p25), or Hoechststain (indicating cortical cells).

Gamma exposure also reduced CKp-25-induced neuron loss and DNA damage inthe hippocampus of subjects. FIG. 107 is a bar graph comparing theamount of NeuN-positive cells as a percentage of the NeuN-positive cellsin CK-control mice for the CK-control mice, untreated CK-p25 Tg mice,CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to the40-Hz light flicker in accordance with some embodiments, and CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker. Thus, thepercentage of the CK-control mice NeuN-positive cells are 100% in theCK-control mice, but closer to 80% in untreated CK-p25 Tg mice,corroborating neuronal loss in the CK-p25 Tg mouse model. Treatment withmemantine with or without exposure to the 40-Hz light flicker preventedsome neuronal loss in CK-p25 Tg mice compared to the untreated group,which prevented the least neuronal loss in CK-p25 Tg mice. Thus, FIG.107 illustrates how 40-Hz visual flicker treatment in accordance withsome embodiments can preserve neurons in the hippocampus.

FIG. 108 is bar graph comparing the amount of γH2AX-positive cells inCK-control mice, untreated CK-p25 Tg mice, CK-p25 Tg mice treated withmemantine, CK-p25 Tg mice exposed to the 40-Hz light flicker inaccordance with some embodiments, and CK-p25 Tg mice treated with bothmemantine and the 40-Hz light flicker. Cells positive for γH2AX werenon-existent in CK-control mice, but very high in untreated CK-p25 Tgmice, indicating high amounts of DSB and other DNA damage. Treatmentwith memantine reduced the amount of γH2AX-positive cells in CK-p25 Tgmice compared to the untreated group. Exposure to the 40-Hz lightflicker in accordance with some embodiments resulted in betterreductions of γH2AX-positive cells in CK-p25 Tg mice. Thus, FIG. 108illustrates how 40-Hz visual flicker treatment in accordance with someembodiments can reduce DNA damage in the hippocampus. However,combination of memantine and exposure to the 40-Hz light flickersignificantly increased the number of γH2AX-positive cells in CK-p25 Tgmice.

FIG. 109 is a series of images illustrating hippocampus samplesrepresentative of subjects in each group labeled with Hoechst stain(indicating cortical cells), GFP (indicating CK-p25), γH2AX (indicatingDSB), or NeuN (indicating neurons).

Gamma exposure and/or administration in accordance with some embodimentswas shown to preserve synapses and/or reduce synaptic losses. Changes insynaptic connectivity may be quantified using specific markers forglutamatergic synapses (e.g., VGluT1, VGluT2, PSD95, and GluR2) andGABAergic synapses (e.g., GAD and VGAT).

For example, gamma exposure reduced CKp-25-induced synaptic loss in thevisual cortex of subjects. FIG. 110 is a bar graph comparing the punctadensity of glutamatergic synapses (using VGluT1) and GABAergic synapses(using GAD65) as a percentage of the baseline synaptic puncta density inCK-control mice for the CK-control mice, untreated CK-p25 Tg mice,CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to the40-Hz light flicker in accordance with some embodiments, and CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker.

Gamma exposure also reduced CKp-25-induced synaptic loss and evenincreased synaptic puncta density in the somatosensory cortex ofsubjects. FIG. 111 is a bar graph comparing the puncta density ofglutamatergic synapses (using VGluT1) and GABAergic synapses (usingGAD65) as a percentage of the baseline synaptic puncta density inCK-control mice for the CK-control mice, untreated CK-p25 Tg mice,CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to the40-Hz light flicker in accordance with some embodiments, and CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker.

Gamma exposure also reduced CKp-25-induced synaptic loss in the insularcortex of subjects. FIG. 112 is a bar graph comparing the puncta densityof glutamatergic synapses (using VGluT1) and GABAergic synapses (usingGAD65) as a percentage of the baseline synaptic puncta density inCK-control mice for the CK-control mice, untreated CK-p25 Tg mice,CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to the40-Hz light flicker in accordance with some embodiments, and CK-p25 Tgmice treated with both memantine and the 40-Hz light flicker.

FIG. 113A is an image illustrating a representative sample with aHoechst stain (indicating cortical cells). FIG. 113B is an imageillustrating VGluT1 (indicating glutamatergic synapses) in therepresentative sample. FIG. 113C is an image illustrating GAD65(indicating GABAergic synapses) in the representative sample. FIG. 113Dis a merged image illustrating Hoechst stain, VGluT1, and GAD65 in therepresentative sample. FIGS. 113E and 113F illustrate a method of punctaquantification using GAD65. FIG. 113E is a binary image of the GAD65converted from FIG. 113C. ImageJ software (available from the U.S.National Institutes of Health, Bethesda, Md.) was used to quantify thebinary image, as shown in FIG. 113F.

A study was conducted to examine whether gamma exposure and/oradministration in accordance with some embodiments affects brainvasculature. Mice were placed in a dark box and exposed to either 40-Hzlight-emitting diode (LED) flicker or constant light off (dark) for onehour. Following stimulation, the mice were sacrificed and perfused.Brain sections were stained with lectin linked to a fluorophore tofluorescently tag blood vessels. Using confocal imaging, changes invasculature size (i.e., blood vessel diameter) were measured.Vasodilation was observed following one hour of 40-Hz LED flicker.

FIG. 128A is a series of representative immunofluorescence imagesillustrating enlarged vasculature in the visual cortex in accordancewith some embodiments. FIG. 128B is a bar graph depicting blood vesseldiameter in the visual cortex and illustrating an increase in bloodvessel diameter following gamma exposure in accordance with someembodiments.

Thus, gamma exposure and/or administration was demonstrated to provideanatomical (e.g., prevention and/or reduction of brain weight loss andenlargement of vasculature), morphology (e.g., prevention and/orreduction of aberrant ventricle expansion and cortical layer thicknessloss), cellular (e.g., prevention and/or reduction of neuronal loss),and molecular (e.g., prevention and/or reduction of DNA damage andsynaptic loss) benefits.

Furthermore, gamma exposure and/or administration was shown to beneuroprotective. Following gamma treatment, the CK-p25 Tg mousemodel—which otherwise exhibits increased Aβ peptide levels, profoundneuronal loss, DNA damage, synaptic loss, tau hyper-phosphorylation,long-term potentiation deficits, and severe cognitive/memoryimpairment—showed relative preservation of neuronal structure and/orfunction (e.g., maintenance/prevention of disease measures and/orreduced/slowed disease progression) and, in some cases, suggestedimprovement of neuronal structure and/or function.

Auditory Stimulation at Gamma Frequency Non-Invasively InducedMicroglial Changes in Subjects.

In some embodiments, gamma exposure and/or administration includesauditory stimulation. The auditory stimulation may include sound pulsesor clicks. A sound stimulus may include a click train of about 35 soundpulses or clicks per second (clicks/s) to about 45 clicks/s. FIG. 114 isa stimulus diagram illustrating a click-train stimulus in accordancewith some embodiments. The stimulus in FIG. 114 has a click frequency of40 clicks/s, with 25 ms between each click, and each click having aduration of 1 ms.

In some embodiments, a sound stimulus has a frequency of about 10 Hz toabout 100 kHz, about 12 Hz to about 28 kHz, about 20 Hz to about 20 kHz,and/or about 2 kHz to about 5 kHz. For example, each sound pulse orclick in a click train may have a frequency of about 10 kHz.

In some embodiments, a sound stimulus has a sound pressure level ofabout 0 dB to about 85 dB, about 30 dB to about 70 dB, and/or about 60dB to about 65 dB. For example, each sound pulse or click in a clicktrain may have a sound pressure level of about 65 dB.

Auditory gamma stimulation was shown to induce microglial cell-statechanges in subjects according to some embodiments. A study was conductedto examine whether auditory gamma exposure and/or administration inducesmicroglial activation in the auditory cortex of subjects in accordancewith some embodiments. A 40-Hz click-train stimulus similar to FIG. 114was used, the stimulus having a click frequency of about 40 clicks/swith each click having a duration of about 1 ms at a tone of about 10kHz and about 60-65 dB. The click-train stimulus was hypothesized toentrain PV+ interneurons in the auditory cortex, thereby exogenouslyregulating gamma oscillations in the auditory cortex.

FIG. 115 is a flow diagram illustrating the study. In FIG. 115, WT micewere housed in their home cage 11500. For one hour per day, for sevenconsecutive days (Days 1-7), the mice were moved to a behavior box(i.e., a soundproof chamber) 11502. While in the behavior box 11502, afirst group of mice was exposed to silence, and a second group of micewas exposed to the click-train stimulus in accordance with someembodiments. After each hour in the behavior box 11502, the mice werereturned to their home cage 11500. On Day 8, the mice were sacrificedfor tissue collection and staining 11504.

The tissue was examined for a level of microglial cells, morphologicchanges in the microglial cells, and microglial activation, as indicatedby soma size. FIG. 116A is a bar graph depicting the average number ofmicroglia in mice exposed to silence (No Stim) compared to mice exposedto the click-train stimulus (Stim). More microglial cells were observedin the mice exposed to the click-train stimulus in accordance with someembodiments. FIG. 116B is a bar graph depicting the average fold changeof projection length of microglia in mice exposed to silence (No Stim)compared to mice exposed to the click-train stimulus (Stim). The averagefold change of the length of the microglia projections was significantlyless in the mice exposed to the click-train stimulus in accordance withsome embodiments. FIG. 116C is a bar graph depicting the average foldchange of soma size of microglia in mice exposed to silence (No Stim)compared to mice exposed to the click-train stimulus (Stim). The averagefold change of the soma size of the microglia was significantly greaterin the mice exposed to the click-train stimulus, indicating greatermicroglial activation in accordance with some embodiments.

FIG. 117A is a representative image of the microglial cells in miceexposed to silence. FIG. 117B is a representative image of themicroglial cells in mice exposed to the click-train stimulus inaccordance with some embodiments. The projections and soma of themicroglia are visibly different between FIG. 117A and FIG. 117B inaccordance with some embodiments. FIG. 118A is a magnified image fromFIG. 117B of a microglial cell from a mouse exposed to the click-trainstimulus in accordance with some embodiments. One projection 11800 ofthe microglial cell has been highlighted. Meanwhile, FIG. 118B is amagnified image from FIG. 117A of a microglial cell from a mouse exposedto silence. One projection 11802 of the microglial cell has beenhighlighted to show its length relative to the comparatively shorterprojection 11800 of the microglial cell from a mouse exposed to theclick-train stimulus in accordance with some embodiments.

FIG. 119A is a magnified image from FIG. 117B of a microglial cell froma mouse exposed to the click-train stimulus in accordance with someembodiments. The area of soma 11900 of the microglial cell has beenhighlighted. Meanwhile, FIG. 119B is a magnified image from FIG. 117A ofa microglial cell from a mouse exposed to silence. The area of soma11902 of the microglial cell has been highlighted to show its sizerelative to the comparatively larger soma 11900 of the microglial cellfrom a mouse exposed to the click-train stimulus, thus indicatinggreater microglial activation in accordance with some embodiments.

Auditory gamma stimulation was shown to induce microglialactivation-like phenotype in subjects according to some embodiments. Thestudy of FIG. 115 was repeated with 5×FAD Tg mice in accordance withsome embodiments. The tissue was examined for a level of microglialcells, morphologic changes in the microglial cells (e.g., projectionlength), and microglial activation (e.g., as indicated by soma size).FIG. 120A is a bar graph depicting the average number of microglia perfield of image in mice exposed to silence (No Stim) compared to miceexposed to the click-train stimulus (Stim). Significantly moremicroglial cells were observed in the mice exposed to the click-trainstimulus in accordance with some embodiments. FIG. 120B is a bar graphdepicting the average fold change in soma size of microglia in miceexposed to silence (No Stim) compared to mice exposed to the click-trainstimulus (Stim). The average fold change in soma size was significantlygreater in the mice exposed to the click-train stimulus, indicatinggreater microglial activation in accordance with some embodiments. FIG.120C is a bar graph depicting the average fold change in projectionlength of microglia in mice exposed to silence (No Stim) compared tomice exposed to the click-train stimulus (Stim). The average fold changein projection length was significantly less in the mice exposed to theclick-train stimulus in accordance with some embodiments.

FIG. 121A is a representative image of the microglial cells in miceexposed to silence. FIG. 121B is a representative image of themicroglial cells in mice exposed to the click-train stimulus inaccordance with some embodiments. The projections and soma of themicroglia are visibly different between FIG. 121A and FIG. 121B withcomparatively shorter projection length and larger soma size in themicroglia from a mouse exposed to the click-train stimulus in accordancewith some embodiments.

Auditory Stimulation at Gamma Frequency Non-Invasively Reduces Aβ in theAuditory Cortex and Hippocampus of Subjects

Auditory gamma stimulation was shown to decrease levels of Aβ insubjects according to some embodiments. The study of FIG. 115 wasrepeated with six-month 5×FAD Tg mice in accordance with someembodiments. On Day 8 the auditory cortex and hippocampus weredissected. ELISA was used to measure levels of soluble and insoluble Aβisoforms, including isoform Aβ₁₋₄₀ peptide and isoform Aβ₁₋₄₂ peptide.Insoluble Aβ was treated with 5M guanidine-HCl for three hours in orderto solubilize plaques.

Auditory gamma stimulation was shown to decrease levels of soluble Aβ insubjects according to some embodiments. FIG. 122A is a bar graphdepicting much smaller levels of soluble isoform Aβ₁₋₄₂ peptide in theauditory cortex of mice exposed to the click-train stimulus (Stim)relative to levels of soluble isoform Aβ₁₋₄₂ peptide in the auditorycortex of mice exposed to silence (No Stim) in accordance with someembodiments.

FIG. 122B is a bar graph depicting smaller levels of soluble isoformAβ₁₋₄₀ peptide in the auditory cortex of mice exposed to the click-trainstimulus (Stim) relative to levels of soluble isoform Aβ₁₋₄₀ peptide inthe auditory cortex of mice exposed to silence (No Stim) in accordancewith some embodiments.

FIG. 122C is a bar graph depicting much smaller levels of solubleisoform Aβ₁₋₄₂ peptide in the hippocampus of mice exposed to theclick-train stimulus (Stim) relative to levels of soluble isoform Aβ₁₋₄₂peptide in the hippocampus of mice exposed to silence (No Stim) inaccordance with some embodiments.

FIG. 122D is a bar graph depicting smaller levels of soluble isoformAβ₁₋₄₀ peptide in the hippocampus of mice exposed to the click-trainstimulus (Stim) relative to levels of soluble isoform Aβ₁₋₄₀ peptide inthe hippocampus of mice exposed to silence (No Stim) in accordance withsome embodiments.

Auditory gamma stimulation was shown to decrease levels of insoluble Aβin subjects according to some embodiments. FIG. 123A is a bar graphdepicting much smaller levels of insoluble isoform Aβ₁₋₄₂ peptide in theauditory cortex of mice exposed to the click-train stimulus (Stim)relative to levels of insoluble isoform Aβ₁₋₄₂ peptide in the auditorycortex of mice exposed to silence (No Stim) in accordance with someembodiments.

FIG. 123B is a bar graph depicting smaller levels of insoluble isoformAβ₁₋₄₀ peptide in the auditory cortex of mice exposed to the click-trainstimulus (Stim) relative to levels of insoluble isoform Aβ₁₋₄₀ peptidein the auditory cortex of mice exposed to silence (No Stim) inaccordance with some embodiments.

FIG. 123C is a bar graph depicting much smaller levels of insolubleisoform Aβ₁₋₄₂ peptide in the hippocampus of mice exposed to theclick-train stimulus (Stim) relative to levels of insoluble isoformAβ₁₋₄₂ peptide in the hippocampus of mice exposed to silence (No Stim)in accordance with some embodiments.

FIG. 123D is a bar graph depicting smaller levels of insoluble isoformAβ₁₋₄₀ peptide in the hippocampus of mice exposed to the click-trainstimulus (Stim) relative to levels of insoluble isoform Aβ₁₋₄₀ peptidein the hippocampus of mice exposed to silence (No Stim) in accordancewith some embodiments.

FIG. 124A is a representative image of the microglial cells in 5×FADmice exposed to the click-train stimulus in accordance with someembodiments. FIG. 124B is a representative image of the microglial cellsin 5×FAD mice exposed to silence. The projections and soma of themicroglia are visibly different between FIG. 124A and FIG. 124B withcomparatively shorter projection length and larger soma size in themicroglia from a 5×FAD mouse exposed to the click-train stimulus inaccordance with some embodiments.

FIG. 124C is a representative image of the microglial cells in WT miceexposed to silence. FIG. 124D is a representative image of themicroglial cells in WT mice exposed to the click-train stimulus inaccordance with some embodiments. The projections and soma of themicroglia are visibly different between FIG. 124C and FIG. 124D withcomparatively shorter projection length and larger soma size in themicroglia from a WT mouse exposed to the click-train stimulus inaccordance with some embodiments.

Thus, according to some embodiments, non-invasive auditory stimulationat a gamma frequency promoted gamma oscillations and a profoundreduction in AD-associated pathology in the auditory cortex and thehippocampus.

Auditory Stimulation at Gamma Frequency Had Positive Effects on SubjectBehavior.

Auditory gamma stimulation was shown to improve recognition in subjectsaccording to some embodiments. FIG. 125A is a flow diagram illustratinga novel object recognition test performed using 5×FAD mice exposed tothe click-train stimulus in accordance with some embodiments and 5×FADmice exposed to silence. The test assesses an ability of a subject torecognize novel from familiar objects (i.e., recognition memory) basedon the tendency of rodents to spend more time exploring a novel objectthan a familiar object. A recognition index RI was used to compare thesubjects:

$\begin{matrix}{{RI} = \frac{\left( {{time}\mspace{14mu} {with}\mspace{14mu} {new}\mspace{14mu} {object}} \right)}{\left( {{time}\mspace{14mu} {with}\mspace{14mu} {new}\mspace{14mu} {object}} \right) + \left( {{time}\mspace{14mu} {with}\mspace{14mu} {familiar}\mspace{14mu} {object}} \right)}} & (15)\end{matrix}$

In FIG. 125A, 5×FAD mice were habituated to an environment 12500. Attime T1, two novel objects were introduced 12502. Then at time T2,following one hour of rest, the mice were exposed to one familiar objectand one novel object 12504, 12506 for one hour. FIG. 125B is a bar graphdepicting the results of the novel object recognition test in which themice exposed to the click-train stimulus had higher RI, indicating thatthe mice exposed to the click-train stimulus spent much more time withthe new object than the familiar object due to better recognition memoryin accordance with some embodiments.

Auditory gamma stimulation was shown to improve discrimination insubjects according to some embodiments. FIG. 126A is a flow diagramillustrating a novel object location test performed using 5×FAD miceexposed to the click-train stimulus in accordance with some embodimentsand 5×FAD mice exposed to silence. The test assesses spatial memoryand/or discrimination based on the tendency of rodents to spend moretime exploring a newly located object. A recognition index RI was usedto compare the subjects:

$\begin{matrix}{{RI} = \frac{\left( {{time}\mspace{14mu} {with}\mspace{14mu} {newly}\mspace{14mu} {located}\mspace{14mu} {object}} \right)}{\begin{matrix}{\left( {{time}\mspace{14mu} {with}\mspace{14mu} {newly}\mspace{14mu} {located}\mspace{14mu} {object}} \right) +} \\\left( {{time}\mspace{14mu} {with}\mspace{14mu} {previously}\mspace{14mu} {located}\mspace{14mu} {object}} \right)\end{matrix}}} & (16)\end{matrix}$

In FIG. 126A, 5×FAD mice were habituated to an environment 12600. Attime T1, two objects were introduced at first locations 12602. Then attime T2, following one hour of rest, the mice were exposed to one of theobjects at its first location and the other object located at a newsecond location 12604, 12606 for one hour. FIG. 126B is a bar graphdepicting the results of the novel object location test in which themice exposed to the click-train stimulus had higher RI, indicating thatthe mice exposed to the click-train stimulus spent much more time withthe object that moved than the object that stayed in the same locationdue to better spatial memory and/or discrimination in accordance withsome embodiments.

Auditory gamma stimulation was shown to improve spatial memory insubjects according to some embodiments. A Morris water maze test wasperformed using 5×FAD mice exposed to the click-train stimulus inaccordance with some embodiments and 5×FAD mice exposed to silence. Asdescribed above, the test assesses spatial and/or reference memory basedon distal cues used by subjects to navigate from start locations aroundthe perimeter of an open swimming arena to locate a submerged escapeplatform. The test was assessed across repeated trials, and spatialand/or reference memory was determined by preference for the platformarea when the platform is absent.

FIG. 127A is a plot depicting average latency to find the platform bythe mice exposed to silence (No Stim) and the mice exposed to theclick-train stimulus (Stim) on each day in accordance with someembodiments. FIG. 127B is a bar graph depicting the results of a probetest in which the platform was removed. The mice exposed to theclick-train stimulus spent more time searching for the missing platformin the target quadrant than did the mice exposed to silence, thusindicating that the mice exposed to the click-train stimulus had betterspatial and/or reference memory in accordance with some embodiments.

Thus, according to some embodiments, non-invasive auditory stimulationat a gamma frequency induced microglial activation, reducedAD-associated (e.g., Aβ) pathology, and significantly amelioratedcognitive deficits (in, e.g., recognition, discrimination, and spatialmemory). With easy and accessible options for administration (includingself-administration), auditory gamma stimulation has the potential forvast commercial applications, including but not limited to applicationsfor home or mobile use (e.g., using noise-canceling headphones). Inaddition to self-administration potential, clinicians and/or researchersmay administer a stimulation paradigm to subjects ranging from animalmodels to human patients in accordance with some embodiments. Cliniciansand/or researchers may find it useful to combine auditory gammastimulation with various forms of monitoring. For example, a therapeuticsession may include locating a subject in a sound proof room orsupplying the subject with noise-canceling headphones or another deviceto limit interference. The subject may be monitored during thestimulation using, for example, functional magnetic resonance imaging(fMRI) for any beneficial brain-state changes.

Experimental Methods

Animals

All animal work was approved by the Committee for Animal Care of theDivision of Comparative Medicine (Massachusetts Institute of Technology,Cambridge, Mass.). Adult (three-month-old) male double Tg 5×FAD Cre micewere produced by crossing 5×FAD Tg mice with the Tg PV or CW2 promoterdriven Cre line. Adult (5-month-old) male and female APP/PS1 mice weregifted from the Tonegawa Laboratory (Massachusetts Institute ofTechnology, Cambridge, Mass.). Adult (4-month-old) male TauP301S micewere obtained from the Jackson Laboratory. Aged WT mice (8-month-old,C57Bl/6) were obtained from the Jackson Laboratory (Bar Harbor, Me.).Mice were housed in groups of 3-5 on a standard 12 hours light/12 hoursdark cycle, and all experiments were performed during the light cycle.Food and water were provided ad libitum unless otherwise noted.Littermates were randomly assigned to each condition by theexperimenter. Experimenter was blind to animal genotypes during tissueprocessing and electrophysiological recording and analysis. No animalswere excluded from analysis.

AAV Vectors

Adeno-associated viral particles of serotype 5 were obtained from theVector Core Facility (The University of North Carolina, Chapel Hill,N.C.). The AAV5 virus contained ChR2 fused to enhanced yellowfluorescent protein (EYFP) in a double-floxed, inverted,open-reading-frame (DIO) driven by the EF1α promoter (see, e.g., FIG.9). An AAV DIO EYFP construct was used as a control.

Surgical Procedures

Three-month-old 5×FAD/PV-Cre or CW2 mice were anesthetized with anintraperitoneal injection of a mixture of ketamine (1.1 mg kg⁻¹) andxylazine (0.16 mg kg⁻¹). A small craniotomy was made 2.0 mm posterior tobregma and 1.8 mm lateral to the midline on the left side. Virus wasdelivered through a small durotomy by a glass micropipette attached to aQuintessential Stereotaxic Injector™ (available from Stoelting Co., WoodDale, Ill.). The glass micropipette was lowered to 1.2 mm below thebrain surface. A bolus of 1 μl of virus (AAV DIO ChR2—EYFP or AAV DIOEYFP; 2×1012 viral molecules per ml) was injected into the CA1 region ofthe hippocampus at 0.075 μl min⁻¹. The pipette remained in place for 5min following the injection before being retracted from the brain. Aunilateral optical fiber implant (300 μm core diameter, available fromThorlabs Inc., Newton, N.J.) was lowered to 0.9 mm below the brainsurface about the injection site. Two small screws anchored at theanterior and posterior edges of the surgical site were bound with dentalglue to secure the implant in place. For electrophysiological recordingsadult (three-month-old) male 5×FAD/PV-Cre bi-transgenic mice and 5×FADnegative littermates (for CA1 recordings), or 5×FAD and their WTlittermates (for visual cortex recordings) mice were anesthetized usingisoflurane and placed in a stereotactic frame. The scalp was shaved,ophthalmic ointment (e.g., Puralube® Vet Ointment (DechraPharmaceuticals PLC, Northwich, United Kingdom)) was applied to theeyes, and Betadine® antiseptic (available from Purdue Products L.P.,Stamford, Conn.) and 70% ethanol were used to sterilize the surgicalarea. For CA1 recordings, a craniotomy (in mm, from bregma: −2 A/P, 1.8M/L) was opened to deliver 1 μL of virus to CA1 (as described above).The target craniotomy site for LFP recordings was marked on the skull(in mm, from bregma: −3.23 A/P, 0.98 M/L for CA1 and 2.8 A/P, 2.5 M/Lfor visual cortex), three self-tapping screws (e.g., F000CE094,available from Morris Precision Screws and Parts, Southbridge, Mass.)were attached to the skull, and a custom stainless steel head plate wasaffixed using dental cement (e.g., C&B Metabond®, available from ParkellInc., Edgewood, N.Y.). On the day of the first recording session, adental drill was used to open the LFP craniotomies (e.g., 300-400 μmdiameter) by first thinning the skull until approximately 100 μm thick,and then using a 30 gauge needle to make a small aperture. Thecraniotomy was then sealed with a sterile silicone elastomer (e.g.,Kwik-Sil™ adhesive, available from World Precision Instruments, Inc.,Sarasota, Fla.) until recording that day and in between recordingsessions.

Optogenetic Stimulation Protocol

Two to four weeks following virus injection and implant placement, whichprovides time for the mice to recover and undergo behavior training foranimals used for electrophysiology, and the virus to express in theneurons, hippocampal CA1 neurons were optogenetically manipulated. A 200mW 4793 nm DPSS laser was connected to a patch cord with a fiberchannel/physical contact connector at each end. During the experiment, 1mW (measured from the end of the fiber) of optical stimulation wasdelivered for one hour. For molecular and biochemical analyses, eachanimal received one of three stimulation protocols: 8 Hz, 40 Hz, orrandom stimulation (light pulses were delivered with a random intervaldetermined by a Poisson process with an average frequency of 40 Hz) orfor electrophysiological recordings each animal received all stimulationconditions interleaved during recordings.

Visual Stimulation Protocol

Fifteen minutes prior to the experiment 5×FAD mice were treated withsaline (Control) or picrotoxin (0.18 mg/kg). For molecular andbiochemical analyses mice were then placed in a dark chamber illuminatedby an LED bulb and exposed to one of five stimulation conditions: dark,light, 20-Hz flicker, 40-Hz flicker, or 80-Hz flicker (12.5 ms light on,12.5 ms light off) for one hour (see, e.g., FIG. 43A). Forelectrophysiological recordings each animal received dark, light, 40-Hzflicker, or random (light pulses were delivered with a random intervaldetermined by a Poisson process with an average interval of 40 Hz)stimulation conditions interleaved in 10 s blocks during recordings.

Behavior Training and Virtual Reality Environment (VR) forElectrophysiology

For CA1 recordings, headfixed animals ran on an 8″ spherical treadmillsupported by an air cushion through a virtual reality environment, asdescribed in Harvey et al. The motion of the spherical treadmill wasmeasured by an optical mouse and fed into virtual reality software,running in the MATLAB® computing environment (software version 2013b,available from MathWorks, Natick, Mass.). The virtual environmentconsisted of a linear track with two small enclosures at the ends wherethe animal could turn. Animals were rewarded with sweetened condensedmilk (diluted 1:2 in water) at each end of the track for alternatingvisits to each end of the track. Animals learned to run on the virtuallinear track over approximately one week. The animals were left torecover from the surgery for one week, and habituated to handling forone to two days before behavioral training began. To learn to maneuveron the treadmill and get comfortable in the testing environment, on thefirst two days of training the animals were placed on the sphericaltreadmill with the virtual reality system off and were rewarded withundiluted sweetened condensed milk. On the second day of training on thespherical treadmill, animals' food was restricted to motivate them torun. Animals were restricted to no more than 85% of their baselineweight and typically weighed over 88% of their baseline weight. From thethird day until the end of training (typically 5-seven days) the animalswere placed on the treadmill for increasing amounts of time (30 min to 2hours) running in the VR linear track. Animals were rewarded withdiluted (1:2) sweetened condensed milk at the end of the linear trackafter traversing the length of the track. Between recording sessions,animals were given refresher training sessions to maintain behavioralperformance. For visual cortex recordings, animals ran on the sphericaltreadmill while exposed to dark, light, or light flickering conditions(described below in data acquisition). Prior to recordings animalslearned to maneuver on the treadmill and get comfortable in the testingenvironment by being placed on the spherical treadmill (with the virtualreality system off) and receiving reward of undiluted sweetenedcondensed milk.

Electrophysiology Data Acquisition

For optogenetic stimulation of CA1 during recording, a 300 μm coreoptical fiber was advanced through the craniotomy used to deliver virusto CA1 to a depth of 900 μm into the brain. Light pulses that were 1 msand 1 mW (measured from the end of the fiber) were delivered via a 473nm DPSS (diode pumped solid state) laser (as described above). To avoidphotoelectric artifacts, neural activity was recorded with glasselectrodes. LFP electrodes were pulled from borosilicate glass pipettes(e.g., available from Warner Instruments, Hamden, Conn.) on afilament-based micropipette puller (e.g., a P-97 FlamingBrown™micropipette puller, available from Sutter Instrument Co., Novato,Calif.), to a fine tip, which was then manually broken back to adiameter of approximately 10-20 μm and then filled with sterile saline.For CA1 recordings the LFP electrode was advanced through the LFPrecording craniotomy at an angle 60 degrees posterior to the coronalplane and 45 degrees inferior to the horizontal plane until clearelectrophysiological signatures of the hippocampal stratum pyramidalelayer were observed (approximately 600-1000 μV theta waves while theanimal was running, clearly distinguishable SWR during immobility,multiple spikes greater than 150 μV, see, e.g., FIGS. 2A-2B). For visualcortex recordings the LFP electrode was advanced vertically through theLFP recording craniotomy to a depth of 600-900 μm and multiple spikesgreater than 150 μV were observed. Data was acquired with a samplingrate of 20 kHz and bandpass filtered 1 Hz-1 kHz. Animals ran on thespherical treadmill or rested for prolonged periods. For optogeneticsimulation sessions, data was recorded for 30 minutes before anystimulation began. Then stimulation was delivered at gamma (40 Hz),random (as described under optogenetic stimulation), or theta (8 Hz)frequency for 10 s periods interleaved with 10 s baseline periods (nostimulation). In two animals, stimulation of each type or baseline wasdelivered for 5 min periods instead of 10 s periods. Each 30 minutes ofstimulation recordings were followed by 5-30 minutes of recording withno stimulation. For visual light flicker simulation sessions, LED striplights surrounding the animal lights were flickered at gamma (40 Hz),random (described above in Visual stimulation protocol), theta (8 Hz),or 20 Hz frequency for 10 s periods, or were on continuously for 10 speriods, interleaved with 10 s periods with lights off. A few recordingswere made above the brain surface during light flicker to ensure thatthe lights did not create electrical or photoelectric noise duringrecording. Recording sessions were terminated after approximately 3-5hours. Animals were 3-4 months old at the time of recording. Analysis ofelectrophysiology recordings

Spike Detection

Spikes were detected by thresholding the 300-6000 Hz bandpassed signal.Threshold was the median of the filtered signal plus five times a robustestimator of the standard deviation of the filtered signal(median/0.675) to avoid contamination of the standard deviation measureby spikes (see, e.g., Rossant et al., “Spike Sorting for Large, DenseElectrode Arrays,” bioRxiv doi: dx_doi_org_10.1101_015198 (Feb. 16,2015)).

Local Field Potential (LFP)

Recorded traces were downsampled to 2 kHz and then bandpass-filteredbetween 1 to 300 Hz.

Theta and SWR Detection

Activity across the hippocampal network changes markedly when animalsrun or sit quietly and these changes are often referred to as differentnetwork states. These network states are clearly distinguishable by thepresence or absence of LFP oscillations in different frequency bands.When animals ran, large theta (4-12 Hz) oscillations in CA1 wereobserved as others have shown (see, e.g., FIG. 2A). When animals satquietly, theta oscillations were no longer visible and SWRs, highfrequency oscillations of 150-250 Hz that last around 50-100 ms and areassociated with bursts of population activity (see., e.g., FIG. 2B),were recorded. SWRs were detected (see, e.g., FIGS. 4A, 4B, 5A, 5B, 6A,6B, 7B, and 8) when the envelope amplitude of the filtered trace wasgreater than four standard deviations above the mean for at least 15 ms.The envelope amplitude was calculated by taking the absolute value ofthe Hilbert transform of the filtered LFP. It has been confirmed thatresults disclosed herein held when using a higher threshold for SWRdetection, 6 standard deviations above the mean, which detects largerSWRs (see, e.g., FIGS. 6C and 7C). To detect theta (see, e.g., FIGS. 3Aand 3C), the LFP was bandpass filtered for theta (4-12 Hz), delta (1-4Hz), and beta (12-30 Hz) using an FIR equiripple filter. The ratio oftheta to delta and beta (‘theta ratio’) was computed as the thetaenvelope amplitude divided by the sum of the delta and beta envelopeamplitudes. Theta periods were classified as such when the theta ratiowas greater than one standard deviation above mean for at least twoseconds and the ratio reached a peak of at least two standard deviationsabove mean. Non-theta periods were classified as such when the thetaratio was less than one for at least two seconds. SWRs, theta periods,and non-theta periods were visually inspected to ensure that thesecriteria accurately detected SWRs, theta periods, and non-theta periods,respectively.

Power Spectrum

Spectral analysis was performing using multitaper methods (e.g., Chronuxopen source software, available from the Mitra Lab in Cold Spring HarborLaboratory, Cold Spring Harbor, N.Y., time-bandwidth product=3, numberof tapers=5). For examining power spectra without stimulation (see,e.g., FIGS. 3A and 3C), only theta periods were included: theta periodsgreater than 5 seconds long were divided into 5 second trials and theaverage power spectral density was computed for each animal over thesetrials. For examining power spectra during optogenetic (see, e.g., FIGS.13A and 6C) and visual stimulation (see, e.g., FIGS. 43B and 43C), datawas divided into 10 second trials of each stimulation condition orbaseline periods, and the average power spectral density was computedfor each animal over these trials.

Gamma During SWRs

Spectrograms were computed using multitaper methods (e.g., Chronux opensource software, available from the Mitra Lab in Cold Spring HarborLaboratory, Cold Spring Harbor, N.Y.). The spectrogram was computed foreach SWR including a window of 400 ms before and after the peak of theSWR. Then a z-scored spectrogram was computed in each frequency bandusing the mean and standard deviation of the spectrogram computed acrossthe entire recording session to create a normalized measure of power inunits of standard deviation (see, e.g., FIGS. 4A, 4B, 5A, and 5B).Instantaneous frequency of gamma oscillations during SWRs was computedby bandpass filtering the LFP for 10-50 Hz, taking the Hilberttransform, then taking the reciprocal of the difference in peaks of thetransformed signal (see, e.g., FIGS. 4A, 5A, and 6B). Gamma powerbefore, during, and after SWRs was computed by filtering the LFP for lowgamma (20-50 Hz) and taking the amplitude of the envelope of the Hilberttransform to get the mean gamma power in 100 ms bins centered on the SWRpeak. This was normalized by the mean and standard deviation of theamplitude of the envelope for the entire recording session to getz-scored gamma power for each bin around each SWR (see, e.g., FIGS. 6Aand 7B). Phase modulation by gamma during SWRs was computed by bandpassfiltering the LFP for gamma (20-50 Hz), taking the Hilbert transform,and determining the phase of the resulting signal for each spike thatoccurred during SWRs (see, e.g., FIG. 7E). To measure differences inphase modulation between 5×FAD and WT animals, resampling was used withreplacement: a subset of 100 spikes from each recording was randomlyselected to create a phase modulation distribution and this was repeated500 times for each recording (see, e.g., FIGS. 6C and 7A). The depth ofmodulation was then measured for the spike-gamma phase distribution bycomputing the difference between the peak and trough divided by the sumof the peak and trough for each distribution (see, e.g., FIGS. 6C and7A). Differences in firing during stimulation: To plot stimulus-evokedmultiunit firing histograms, spikes were binned in 2.5 ms bins for the100 ms after the start of each light on pulse and the fraction of spikesin each bin was computed. Mean and SEM was then computed across alllight on periods. To compute differences in multi-unit firing ratebetween conditions, firing rates were computed for each 10 second periodof stimulation or baseline (total number of spikes divided by durationof period). Differences in firing rate were taken between nearby periodsof the relevant type of stimulation (firing rate in gamma stimulationperiod minus baseline or random periods for optogenetic stimulation,firing rate in gamma stimulation period minus baseline, continuous on,or random periods for light flicker stimulation). Differences from allanimals were plotted in histograms (see, e.g., FIGS. 14A and 44A) andthe median and quartiles of differences per animals were plotted in boxplots (see, e.g., FIGS. 13B and 44A).

Immunohistochemistry

Mice were perfused with 4% paraformaldehyde under deep anesthesia, andthe brains were post-fixed overnight in 4% paraformaldehyde. Brains weresectioned at 40 μm using a vibratome (e.g., Leica VT100S, available fromLeica Biosystems, Buffalo Grove, Ill.). Sections were permeabilized andblocked in PBS containing 0.2% Triton X-100 and 10% normal donkey serumat room temperature for one hour. Sections were incubated overnight at4° C. in primary antibody in PBS with 0.2% Triton X-100 and 10% normaldonkey serum. Primary antibodies were anti-EEA1 (BD TransductionLaboratories™ EEA1 (641057), available from BD Biosciences, San Jose,Calif.), anti-β-amyloid (e.g., β-amyloid (D54D2) XP®, available fromCell Signaling Technology, Danvers, Mass.), anti-Iba1 (e.g., 019-19741,available from Wako Chemicals, Richmond, Va.), anti-parvalbumin (e.g.,ab32895, available from Abcam, Cambridge, Mass.), anti-Rab5(ADI-KAp-GP006-E, available from Enzo Life Sciences Inc., Farmingdale,N.Y.). To confirm ELISA experiments, the anti-Aβ antibody D54D2 was usedbecause it allowed for co-labeling with EEA1 and the anti-Aβ antibody12F4 was used because it does not react with APP allowing adetermination as to whether the labeling was specific to Aβ. Forco-labeling experiments, the anti-Aβ antibody 12F4 (805501, availablefrom BioLegend, San Diego, Calif.) was used. Primary antibodies werevisualized with Alexa-Fluor 488 and Alex-Fluor 647 secondary antibodies(Molecular Probes), neuronal nuclei with Hoechst 33342 (94403, availablefrom Sigma-Aldrich, St. Louis, Mo.). Images were acquired using aconfocal microscope (LSM 710; Zeiss™) at identical settings for allconditions. Images were quantified using ImageJ 1.42q by an experimenterblind to treatment groups. For each experimental condition, at least 2coronal sections from at least 3 animals were used for quantification.For hippocampal CA1 imaging, the analysis was restricted to thepyramidal cell layer, except in the case of Iba1+ cells analysis, wherethe whole field of view was required to image an adequate number ofcells. ImageJ was used to measure the diameter of Iba1+ cell bodies andto trace the processes for length measurement. In addition, the Coloc2plug-in was used to measure co-localization of Iba1 and Aβ. Imaris×648.1.2 (available from Bitplane, Belfast, United Kingdom) was used for3-D rendering. For counting the “plaque number,” deposits greater thanor equal to 10 μm were included.

Clarity

Fixed brains were sliced into 100 uM coronal sections on a vibratome(e.g., Leica VT100S, available from Leica Biosystems, Buffalo Grove,Ill.) in 1×PBS. Sections containing visual cortex were selected, withreference to the Allen Mouse Brain Atlas, and incubated in clearingbuffer (pH 8.5-9.0, 200 mM sodium dodecylsulfate, 20 mM lithiumhydroxide monohydrate, 4 mM boric acid in ddH2O) for 2 hours, shaking at55° C. Cleared sections were washed 3×10 mins in 1×PBST (0.1%Triton-X100/1×PBS) and put into blocking solution (2% bovine serumalbumin/1×PBST) overnight, shaking at RT. Subsequently, three one hourwashes in 1×. PBST were performed, shaking at RT. Sections were thenincubated at 4° C. for 2 days, shaking, with anti-β-amyloid (805501,available from BioLegend, San Diego, Calif.) and anti-Iba1 (WakoChemicals, Richmond, Va.; 019-19741) primary antibodies, diluted to1:100 in 1×PBST. Another set of 3×1 h washes in 1×PBST was conductedbefore sections were incubated for 9 hours, shaking at RT, in 1:1001×PBS diluted secondary antibody mixture. Fragmented Donkey Anti-RabbitAlexa Fluor® 488 (ab175694) and Anti-Mouse 568 (ab150101) secondaryantibodies (both available from Abcam, Cambridge, Mass.) were used tovisualize the primary antibody labeling. Halfway through this incubationperiod, Hoechst 33258 (Sigma-Aldrich; 94403) was spiked into each sampleat a 1:250 final dilution. Sections were then washed overnight in 1×PBS,shaking at RT. Prior to mounting for imaging, slices were incubated inRIMS (Refractive Index Matching Solution: 75 g Histodenz, 20 mL 0.1Mphosphate buffer, 60 mL ddH2O) for one hour, shaking at RT. Tissuesections were mounted onto microscopy slides with coverslips (e.g.,VistaVision™, available from VWR International, LLC, Radnor, Pa.) usingFluoromount G Mounting Medium (Electron Microscopy Sciences, Hatfield,Pa., USA). Images were acquired on a Zeiss™ LSM 880 microscope with theaccompanying Zen Black 2.1 software (Carl Zeiss Microscopy, Jena,Germany). Section overview and cellular level images used for 3-Dreconstruction were taken using a Plan-Apochromat 63×/1.4 Oil DICobjective. Imarisx64 8.1.2 (Bitplane™ (Zurich, Switzerland) was used for3-D rendering and analysis.

Western Blot

Hippocampal CA1 whole cell lysates were prepared using tissue fromthree-month-old male 5×FAD/PV-Cre mice. Tissue was homogenized in 1 mlRIPA (50 mM Tris HCl pH 8.0, 150 mM NaCl, 1% Np-40, 0.5% sodiumdeoxycholate, 0.1% SDS) buffer with a hand homogenizer (Sigma-Aldrich(St. Louis, Mo.)), incubated on ice for 15 min, and rotated at 4° C. for30 min. Cell debris was isolated and discarded by centrifugation at14,000 rpm for 10 minutes. Lysates were quantitated using a nanodrop and25 μg protein was loaded on a 10% acrylamide gels. Protein wastransferred from acrylamide gels to PVDF membranes (e.g., Invitrogen™,available from Thermo Fisher Scientific, Waltham, Mass.) at 100 V for120 min. Membranes were blocked using bovine serum albumin (5% w/v)diluted in TBS:Tween. Membranes were incubated in primary antibodiesovernight at 4° C. and secondary antibodies at room temperature for 90minutes. Primary antibodies were anti-APP (Invitrogen™PAD CT695,available from Thermo Fisher Scientific, Waltham, Mass.), anti-APP(A8967, available from Sigma-Aldrich, St. Louis, Mo.), anti-β-Actin(ab9485, available from Abcam, Cambridge, Mass.). Secondary antibodieswere horseradish peroxidase-linked (e.g., available from GE Healthcare,Marlborough, Mass.). Signal intensities were quantified using ImageJ1.46a and normalized to values of β-actin. Tau protein solubility wasexamined using sequential protein extraction. The detergent insolubletau fraction was probed using an antibody against Tau5 (e.g., AHB0042,available from Thermo Fisher Scientific, Waltham, Mass.).

ELISA

Hippocampal CA1 or VC was isolated from male mice, lysed with PBS or 5MGuanidine HCl, and subjected to Aβ measurement with the use ofmouse/human Aβ₁₋₄₀ or Aβ₁₋₄₂ ELISA kit (e.g., Invitrogen™ available fromThermo Fisher Scientific, Waltham, Mass.) according to themanufacturer's instructions. The tissue was lysed in phosphate-bufferedsaline (PBS) to extract the PBS soluble Aβ fraction. The soluble Aβfraction likely contained monomeric and oligomeric Aβ. Tissue wasfurther treated with guanidine hydrochloric acid (HCl) to extract theinsoluble Aβ fraction.

Genome-Wide RNA Sequencing

Total RNA was extracted from hippocampal CA1 isolates using the RNeasykit (available from Qiagen, Hilden, Germany). Purified mRNA was used forRNA-seq library preparation using the BIOO NEXTflex™ kit (BIOO#5138-08)as per the manufacturer's instructions. Briefly, 1 μg of total mRNA wassubject to a sequential workflow of poly-A purification, fragmentation,first flex strand and second strand synthesis, DNA end-adenylation, andadapter ligation. The libraries were enriched by 15 cycles of PCRreactions and cleaned with Agencourt® AMPure XP magnetic beads(available from Beckman Coulter Genomics, Danvers, Mass.). The qualityof the libraries was assessed using an Advanced Analytical-fragmentAnalyzer. The bar-coded libraries were equally mixed for sequencing in asingle lane on the Illumina HiSeq 2000 platform at the MIT BioMicroCenter (Massachusetts Institute of Technology, Cambridge, Mass.). Theraw fastq data of 50-bp single-end sequencing reads were aligned to themouse mm9 reference genome using TopHat 2.0 software (available from theCenter for Computational Biology at Johns Hopkins University, Baltimore,Md., for aligning RNA-seq reads to mammalian-sized genomes using anultra-high-throughput short read aligner Bowtie, and then analyzing themapping results to identify splice junctions between exons). The mappedreads were processed by Cufflinks 2.2 software (available from theTrapnell Lab at the University of Washington, Seattle, Wash.) with UCSCmm9 reference gene annotation to estimate transcript abundances, andtest for differential expression. Relative abundance of transcript wasmeasured by Fragments Per Kilobase of exon per Million fragments mapped(FPKM). Gene differential expression test between treated and untreatedgroups was performed using the Cuffdiff module (for finding significantchanges in transcript expression, splicing, and promoter use, includedas part of Cufflinks 2.2 software (available from the Trapnell Lab atthe University of Washington, Seattle, Wash.)) with an adjustedp-value<0.05 for statistical significance (GEO accession: GSE77471).

To understand the cellular and molecular mechanisms from the RNA-seqdata, 14 of publicly available RNA-seq datasets were processed forcell-type specific analysis. Additionally, 60 publicly availableneuron-, microglia-, and macrophage-specific RNA-seq datasets underdifferent chemical and genetic perturbations were downloaded andprocessed using TopHat Cufflinks 2.2 software (available from theTrapnell Lab at the University of Washington, Seattle, Wash.) for GSEAstatistical analysis. Gene set enrichment analysis (GSEA) was used todetermine whether a defined gene set from the RNA-seq data issignificantly enriched at either direction of a ranked gene list from aparticular perturbation study. Genes detected in the public RNA-seqdatasets were ranked by log 2 values of fold change (case versuscontrol), from positive to negative values. A defined gene set (in thiscase, up- or down-regulated genes upon gamma treatment) was consideredsignificantly correlated with a perturbation-induced transcriptomicchanges (either up- or down-regulation), when both nominal p-value andFDR q-value were less than 0.05. The sign of calculated normalizedenrichment score (NES) indicates whether the gene set is enriched at thetop or the bottom of the ranked list. The heatmap for differentiallyexpressed genes was generated using a custom R script, and z-scorevalues across all libraries for each gene were calculated based on thegene FPKM values. The box plots for cell-type specificity analysis werealso generated by R program, based on gene FPKM values.

Quantitative RT-PCR

The CA1 was isolated from the hippocampus of three-month-old male5×FAD/PV-Cre mice. Tissue was rapidly frozen using liquid nitrogen andstored at −80° C., and RNA extracted using the RNeasy kit according tothe manufacturer's protocol (Qiagen(Hilden, Germany)). RNA (3 μg) wasDNase I treated (4 U, Worthington Biochemical Corporation (Lakewood,N.J.), purified using RNA Clean and Concentrator-5 Kit (Zymo Research(Irvine, Calif.)) according to manufacturers' instructions and elutedwith 14 μl DEPC-treated water. For each sample, 1 μg RNA was reversetranscribed in a 20 μl reaction volume containing random hexamer mix andSuperscript III reverse transcriptase (50 U, Invitrogen™ available fromThermo Fisher Scientific, Waltham, Mass.) at 50° C. for one hour. Firststrand cDNAs were diluted 1:10 and 1 μl were used for RT-qPCRamplification in a 20 μl reaction (SsoFast™ EvaGreen® Supermix, Bio-Rad)containing primers (0.2 μM). Relative changes in gene expression wereassessed using the 2^(−ΔΔCt) method.

Isolation of microglia from visual cortex. The V1 region was rapidlydissected and placed in ice cold Hanks' Balanced Salt Solution (HBSS)(Gibco™ 14175-095, available from Life Technologies). The tissue wasthen enzymatically digested using the Neural Tissue Dissociation Kit (P)(130-092-628, Miltenyi Biotec, Cambridge, Mass.) according to themanufacturer's protocol, with minor modifications. Specifically, thetissue was enzymatically digested at 37° C. for 15 minutes instead of 35minutes and the resulting cell suspension was passed through a 40 μmcell strainer (352340, Falcon Cell Strainers, Sterile, Corning, N.Y.)instead of a MACS® SmartStrainer, 70 μm. The resulting cell suspensionwas then stained using allophycocyaln (APC)-conjugate CD11b mouse cloneM1/70.15.11.5 (130-098-088, Miltenyi Biotec, Cambridge, Mass.) andphycoerythrin (PE)-conjugated CD45 antibody (e.g., BD Pharmingen™,553081). Fluorescence-activated cell sorting (FACS) was then used topurify CD11b and CD45 positive microglial cells. The cells were sorteddirectly into 1×PBS (see, e.g., FIG. 52A).

Statistics

For electrophysiological data that was not normally distributed, resultsare presented as medians and quartiles unless otherwise noted. Two-sidedWilcoxon rank sum tests for equal medians were performed to determine ifdistributions were significantly different or Wilcoxon signed rank testswere performed to determine if distributions were significantlydifferent from zero as these do not assume data is normally distributed.Variability was similar between the groups that were statisticallycompared. The Bonferroni method was used to correct for multiplecomparisons. Molecular and biochemical results are presented as mean andSEM. Percentages stated in the disclosure are group means. Allstatistical analysis was performed using Prism GraphPad software(GraphPad software Inc., La Jolla, Calif.). Normality was determinedusing the D'Agostino & Pearson omnibus normality test. Variability wassimilar between the groups that were statistically compared. Comparisondata for normally distributed data consisting of two groups was analyzedby two-tailed unpaired t tests. Comparison of data for normallydistributed data consisting of three or more groups was analyzed byone-way ANOVA followed by Tukey's multiple comparisons test. Comparisondata for non-normally distributed data was carried out using MannWhitney tests. The statistical test, exact P values, and sample size (n)for each experiment is specified in the figure legend. Molecular andbiochemical analysis was performed using a minimum of three biologicalreplicates per condition.

Auditory Gamma Stimulus Generation

The following script composed in the MATLAB® programming language(available from MathWorks, Natick, Mass.) illustrates one way togenerate an auditory click-train stimulus in accordance with someembodiments:

click_freq=input(‘Specify Number of Clicks Per Second: ’);%Obtaindesired number of clicks per second from the keyboard click_duration=input(‘Specify Click Duration in Milliseconds: ’);%Obtain desired clickduration from the keyboard sound_freq=input(‘Specify Sound Frequency inHertz: ’);%Obtain desired sound frequency in Hertz from the keyboardsound_duration =input (‘Specify Sound Duration in Seconds: ’);%Obtaindesired sound duration from the keyboard %audio_sample_rate=input(‘Specify Audio Sample Rate in Hertz: ’);%Obtain desired audio samplerate from the keyboard audio_file_name =input (‘Specify Audio File Nameand Extension: ’);%Obtain desired audio file name from the keyboardrfreq=2*pi*sound_freq;%Convert sound frequency to radian frequency %%audio_sample_rate = double(sound_freq*8); %% %% if audio_sample_rate <8192 %% audio_sample_rate = 8192 %% end audio_sample_rate = 200000;%Ts=linspace (0,sound_duration,audio_sample_rate*sound_duration);%Specify sample timesover 4 seconds (default sample rate in 8192 Hz)Ts=0:1/audio_sample_rate:sound_duration;sound_signal=cos(rfreq*Ts);%Calculate the cosine for the entire soundduration pulse_width = click_duration/1000;% pulse width D_1 =pulse_width/2:1/click_freq:max(Ts);% 50Hz repetition freq; note:starting D at width/2 instead of 0 to shift the pulse train to the rightby width/2 and thus start the train at 0 pulse_train_mask = pulstran(Ts,D_1, ‘rectpuls’, pulse_width): %Mask the sound signal with the pulsetrain mask sound_signal_masked = sound_signal.*pulse_train_mask; %Playthe click sound soundsc(sound_signal_masked, audio_sample_rate); %Savethe audio file audiowrite(audio_file_name, sound_signal_masked,audio_sample_rate);

CONCLUSION

While various inventive embodiments have been described and illustratedherein, those of ordinary skill in the art will readily envision avariety of other means and/or structures for performing the functionand/or obtaining the results and/or one or more of the advantagesdescribed herein, and each of such variations and/or modifications isdeemed to be within the scope of the inventive embodiments describedherein. More generally, those skilled in the art will readily appreciatethat all parameters, dimensions, materials, and configurations describedherein are meant to be exemplary and that the actual parameters,dimensions, materials, and/or configurations will depend upon thespecific application or applications for which the inventive teachingsis/are used. Those skilled in the art will recognize, or be able toascertain using no more than routine experimentation, many equivalentsto the specific inventive embodiments described herein. It is,therefore, to be understood that the foregoing embodiments are presentedby way of example only and that, within the scope of the appended claimsand equivalents thereto, inventive embodiments may be practicedotherwise than as specifically described and claimed. Inventiveembodiments of the present disclosure are directed to each individualfeature, system, article, material, kit, and/or method described herein.In addition, any combination of two or more such features, systems,articles, materials, kits, and/or methods, if such features, systems,articles, materials, kits, and/or methods are not mutually inconsistent,is included within the inventive scope of the present disclosure.

The above-described embodiments can be implemented in any of numerousways. For example, embodiments disclosed herein may be implemented usinghardware, software or a combination thereof. When implemented insoftware, the software code can be executed on any suitable processor orcollection of processors, whether provided in a single computer ordistributed among multiple computers.

Further, it should be appreciated that a computer may be embodied in anyof a number of forms, such as a rack-mounted computer, a desktopcomputer, a laptop computer, or a tablet computer. Additionally, acomputer may be embedded in a device not generally regarded as acomputer but with suitable processing capabilities, including a PersonalDigital Assistant (PDA), a smart phone or any other suitable portable orfixed electronic device.

Also, a computer may have one or more input and output devices. Thesedevices can be used, among other things, to present a user interface.Examples of output devices that can be used to provide a user interfaceinclude printers or display screens for visual presentation of outputand speakers or other sound generating devices for audible presentationof output. Examples of input devices that can be used for a userinterface include keyboards, and pointing devices, such as mice, touchpads, and digitizing tablets. As another example, a computer may receiveinput information through speech recognition or in other audible format.

Such computers may be interconnected by one or more networks in anysuitable form, including a local area network or a wide area network,such as an enterprise network, and intelligent network (IN) or theInternet. Such networks may be based on any suitable technology and mayoperate according to any suitable protocol and may include wirelessnetworks, wired networks or fiber optic networks.

The various methods or processes outlined herein may be coded assoftware that is executable on one or more processors that employ anyone of a variety of operating systems or platforms. Additionally, suchsoftware may be written using any of a number of suitable programminglanguages and/or programming or scripting tools, and also may becompiled as executable machine language code or intermediate code thatis executed on a framework or virtual machine.

Also, various inventive concepts may be embodied as one or more methods,of which an example has been provided. The acts performed as part of themethod may be ordered in any suitable way. Accordingly, embodiments maybe constructed in which acts are performed in an order different thanillustrated, which may include performing some acts simultaneously, eventhough shown as sequential acts in illustrative embodiments.

All publications, patent applications, patents, and other referencesmentioned herein are incorporated by reference in their entirety.

All definitions, as defined and used herein, should be understood tocontrol over dictionary definitions, definitions in documentsincorporated by reference, and/or ordinary meanings of the definedterms.

The indefinite articles “a” and “an,” as used herein in thespecification and in the claims, unless clearly indicated to thecontrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in theclaims, should be understood to mean “either or both” of the elements soconjoined, i.e., elements that are conjunctively present in some casesand disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined. Other elements may optionally be presentother than the elements specifically identified by the “and/or” clause,whether related or unrelated to those elements specifically identified.Thus, as a non-limiting example, a reference to “A and/or B”, when usedin conjunction with open-ended language such as “comprising” can refer,in one embodiment, to A only (optionally including elements other thanB); in another embodiment, to B only (optionally including elementsother than A); in yet another embodiment, to both A and B (optionallyincluding other elements); etc.

As used herein in the specification and in the claims, “or” should beunderstood to have the same meaning as “and/or” as defined above. Forexample, when separating items in a list, “or” or “and/or” shall beinterpreted as being inclusive, i.e., the inclusion of at least one, butalso including more than one, of a number or list of elements, and,optionally, additional unlisted items. Only terms clearly indicated tothe contrary, such as “only one of” or “exactly one of,” or, when usedin the claims, “consisting of,” will see, e.g., the inclusion of exactlyone element of a number or list of elements. In general, the term “or”as used herein shall only be interpreted as indicating exclusivealternatives (i.e., “one or the other but not both”) when preceded byterms of exclusivity, such as “either,” “one of,” “only one of,” or“exactly one of” “Consisting essentially of,” when used in the claims,shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “atleast one,” in reference to a list of one or more elements, should beunderstood to mean at least one element selected from any one or more ofthe elements in the list of elements, but not necessarily including atleast one of each and every element specifically listed within the listof elements and not excluding any combinations of elements in the listof elements. This definition also allows that elements may optionally bepresent other than the elements specifically identified within the listof elements to which the phrase “at least one” refers, whether relatedor unrelated to those elements specifically identified. Thus, as anon-limiting example, “at least one of A and B” (or, equivalently, “atleast one of A or B,” or, equivalently “at least one of A and/or B”) canrefer, in one embodiment, to at least one, optionally including morethan one, A, with no B present (and optionally including elements otherthan B); in another embodiment, to at least one, optionally includingmore than one, B, with no A present (and optionally including elementsother than A); in yet another embodiment, to at least one, optionallyincluding more than one, A, and at least one, optionally including morethan one, B (and optionally including other elements); etc.

In the claims, as well as in the specification above, all transitionalphrases such as “comprising,” “including,” “carrying,” “having,”“containing,” “involving,” “holding,” “composed of,” and the like are tobe understood to be open-ended, i.e., to mean including but not limitedto. Only the transitional phrases “consisting of” and “consistingessentially of” shall be closed or semi-closed transitional phrases,respectively, as set forth in the United States Patent Office Manual ofPatent Examining Procedures, Section 2111.03.

1. A method for at least one of preventing, mitigating, and treatingdementia in a subject comprising inducing synchronized gammaoscillations in at least one brain region of the subject.
 2. The methodof claim 1, wherein the synchronized gamma oscillations have a frequencyof about 20 Hz to about 50 Hz.
 3. The method of claim 2, wherein thesynchronized gamma oscillations have a frequency of about 40 Hz.
 4. Themethod of claim 1, wherein the synchronized gamma oscillations areinduced in a cell-type specific manner.
 5. The method of claim 4,wherein the synchronized gamma oscillations correspond to synchronizedactivation of fast-spiking-parvalbumin (FS-PV)-interneurons.
 6. Themethod of claim 1, wherein the synchronized gamma oscillations areinduced in a brain-region specific manner.
 7. The method of claim 6,wherein the synchronized gamma oscillations correspond to synchronizedactivation in at least one of a hippocampus region and a sensory cortexregion.
 8. The method of claim 1, wherein the dementia is associatedwith at least one of Alzheimer's Disease, vascular dementia, frontaltemporal dementia, Lewy Body dementia, and age-related cognitivedecline.
 9. The method of claim 1, wherein the subject is a human.
 10. Amethod for at least one of preventing, mitigating, and treating dementiain a subject comprising providing a stimulus emitting device configuredto emit a stimulus with gamma oscillations for administration of thestimulus to the subject, thereby inducing in vivo synchronized gammaoscillations in at least one brain region of the subject.
 11. The methodof claim 10, wherein the gamma oscillations of the stimulus have afrequency of about 35 Hz to about 45 Hz.
 12. The method of claim 11,wherein the gamma oscillations of the stimulus have a frequency of about40 Hz.
 13. The method of claim 10, wherein the stimulus emitting deviceis at least one of a haptic device, a light emitting device, and a soundemitting device. 14-17. (canceled)
 18. A method for at least one ofmaintaining and reducing an amount of amyloid-β (Aβ) peptide in at leastone brain region of a subject comprising inducing synchronized gammaoscillations in the at least one brain region of the subject. 19-20.(canceled)
 21. The method of claim 18, wherein the synchronized gammaoscillations reduce production of Aβ peptide in the at least one brainregion of the subject.
 22. The method of claim 21, wherein thesynchronized gamma oscillations reduce an amount of at least one ofC-terminal fragments (CTFs) and N-terminal fragments (NTFs) of amyloidprecursor protein (APP) in the at least one brain region of the subject.23. The method of claim 22, wherein the synchronized gamma oscillationsreduce cleavage of APP into CTFs and NTFs by at least one of β-secretase(BACE1) and γ-secretase in the at least one brain region of the subject.24. The method of claim 21, wherein the synchronized gamma oscillationsreduce a number of endosomes in the at least one brain region of thesubject.
 25. (canceled)
 26. The method of claim 18, wherein thesynchronized gamma oscillations promote clearance of Aβ peptide in theat least one brain region of the subject.
 27. The method of claim 26,wherein the synchronized gamma oscillations increase uptake of Aβpeptide by microglia in the at least one brain region of the subject.28-81. (canceled)